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ORCID18th ICMLA 2019: Orlando, FL, USA
- M. Arif Wani, Taghi M. Khoshgoftaar, Dingding Wang, Huanjing Wang, Naeem Seliya:
18th IEEE International Conference On Machine Learning And Applications, ICMLA 2019, Boca Raton, FL, USA, December 16-19, 2019. IEEE 2019, ISBN 978-1-7281-4550-1
Session 1: Machine Learning on Image Processing
- Xinjie Lan, Kenneth E. Barner:
Regularization Learning for Image Recognition. 1-7 - Ki-Seok Chung, Changwoo Lee:
GRAM: Gradient Rescaling Attention Model for Data Uncertainty Estimation in Single Image Super Resolution. 8-13 - Kevin Meng, Yu Meng:
Through-Wall Pose Imaging in Real-Time with a Many-to-Many Encoder/Decoder Paradigm. 14-21 - Sebastian Schrom, Stephan Hasler:
Domain Mixture: An Overlooked Scenario in Domain Adaptation. 22-27 - Gul Rukh Khattak
, Sofia Vallecorsa, Federico Carminati, Gul Muhammad Khan:
Particle Detector Simulation using Generative Adversarial Networks with Domain Related Constraints. 28-33
Session 2: Deep Learning Algorithms (I)
- Shubhendu Kumar Singh, Ruoyu Yang, Amir Behjat, Rahul Rai, Souma Chowdhury, Ion Matei:
PI-LSTM: Physics-Infused Long Short-Term Memory Network. 34-41 - Nina Schaaf, Marco F. Huber, Johannes Maucher:
Enhancing Decision Tree Based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization. 42-49 - Vahid Noroozi, Sara Bahaadini, Samira Sheikhi, Nooshin Mojab, Philip S. Yu:
Leveraging Semi-Supervised Learning for Fairness using Neural Networks. 50-55 - Fabio Marco Johner, Jürgen Wassner:
Efficient Evolutionary Architecture Search for CNN Optimization on GTSRB. 56-61
Session 3: Temporal and Structural Modeling
- Dan Halbersberg, Boaz Lerner:
Temporal Modeling of Deterioration Patterns and Clustering for Disease Prediction of ALS Patients. 62-68 - Changwei Hu, Yifan Hu, Sungyong Seo:
A Deep Structural Model for Analyzing Correlated Multivariate Time Series. 69-74 - Alexander Fuchs, Robin Priewald, Franz Pernkopf:
Recurrent Dilated DenseNets for a Time-Series Segmentation Task. 75-80 - Piyush Yadav, Dibya Prakash Das, Edward Curry:
State Summarization of Video Streams for Spatiotemporal Query Matching in Complex Event Processing. 81-88 - Debashri Roy, Tathagata Mukherjee, Mainak Chatterjee, Eduardo Pasiliao:
RF Transmitter Fingerprinting Exploiting Spatio-Temporal Properties in Raw Signal Data. 89-96
Session 4: Recognition and Detection
- Dimuthu Lakmal, Kumaran Kugathasan, Vishaka Nanayakkara, Suranga Jayasena, Amal Shehan Perera, Lasantha Fernando:
Brown Planthopper Damage Detection using Remote Sensing and Machine Learning. 97-104 - Sunil Bharitkar:
Generative Feature Models and Robustness Analysis for Multimedia Content Classification. 105-110 - Jadisha Yarif Ramírez Cornejo, Hélio Pedrini:
Bimodal Emotion Recognition Based on Audio and Facial Parts Using Deep Convolutional Neural Networks. 111-117
Session 5: Machine Learning on Finance and Marketing
- Tong Sun, Jia Wang, Jing Ni, Yu Cao, Benyuan Liu:
Predicting Futures Market Movement using Deep Neural Networks. 118-125 - Anish Khazane, Jonathan Rider, Max Serpe, Antonia Gogoglou, Keegan E. Hines, C. Bayan Bruss, Richard Serpe:
DeepTrax: Embedding Graphs of Financial Transactions. 126-133 - Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang, Ivan Maksimov, Aleksandr Pletnev, Evgeny Burnaev:
An Industry Case of Large-Scale Demand Forecasting of Hierarchical Components. 134-139 - Chi Zhang, Chetan Gupta, Seiji Joichi, Ahmed K. Farahat, Huijuan Shao:
Risk-Based Dynamic Pricing via Failure Prediction. 140-147
Session 6: Text Analytics
- Nayantara Kotoky, Vijaya V. Saradhi:
Learning to Propose Amendments: Identifying Patterns in the Right to Information Query Log. 148-154 - Sun Sunnie Chung, Michael D'Arcy:
Unsupervised Topic Model Based Text Network Construction for Learning Word Embeddings. 155-161 - Sagnik Sarkar, Maulik Parmar, Sumeet Sandhu:
Entity Set Expansion for Detecting Fashion Trends. 162-167 - Meshal Alfarhood, Jianlin Cheng:
Collaborative Attentive Autoencoder for Scientific Article Recommendation. 168-174
Session 7: Recognition and Detection in Computer Vision
- Michael Stephan, Avik Santra:
Radar-Based Human Target Detection using Deep Residual U-Net for Smart Home Applications. 175-182 - Alexandros Stergiou, Ronald Poppe:
Spatio-Temporal FAST 3D Convolutions for Human Action Recognition. 183-190 - Guilherme Vieira Leite, Gabriel Pellegrino da Silva, Hélio Pedrini:
Fall Detection in Video Sequences Based on a Three-Stream Convolutional Neural Network. 191-195 - Hang Shi, Chengjun Liu:
Moving Cast Shadow Detection in Video Based on New Chromatic Criteria and Statistical Modeling. 196-201 - Sebastian Zepf, Tobias Stracke, Alexander Schmitt, Florian van de Camp, Jürgen Beyerer:
Towards Real-Time Detection and Mitigation of Driver Frustration using SVM. 202-209
Session 8: Multi-agent and Robotics
- Jia Wang, Jiannong Cao, Milos Stojmenovic, Miao Zhao, Jinlin Chen, Shan Jiang:
Pattern-RL: Multi-robot Cooperative Pattern Formation via Deep Reinforcement Learning. 210-215 - Subramanya Nageshrao, Bruno Costa, Dimitar P. Filev:
Interpretable Approximation of a Deep Reinforcement Learning Agent as a Set of If-Then Rules. 216-221 - Tianlin Liu, Xihong Wu, Dingsheng Luo:
A Hierarchical Model for StarCraft II Mini-Game. 222-227 - Matheus Prado Prandini Faria, Rita Maria da Silva Julia, Lidia Bononi Paiva Tomaz:
Evaluating the Performance of the Deep Active Imitation Learning Algorithm in the Dynamic Environment of FIFA Player Agents. 228-233 - Kevin Corder, Keith Decker:
Shapley Value Approximation with Divisive Clustering. 234-239
Session 9: Supervised Learning Applications
- Ramkumar Harikrishnakumar, Alok Dand, Saideep Nannapaneni, Krishna Krishnan:
Supervised Machine Learning Approach for Effective Supplier Classification. 240-245 - Christopher Harris, Y. Andi Trisyono:
Classifying, Detecting, and Predicting Infestation Patterns of the Brown Planthopper in Rice Paddies. 246-251 - Christina L. Ting, Renee Gooding, Richard V. Field Jr., Jacob Caswell:
Reordering Genomic Sequences for Enhanced Classification via Compression Analytics. 252-258
Main Conference Poster Papers
- Rodrigo da Fonseca Silveira, Maristela Holanda, Márcio de Carvalho Victorino, Marcelo Ladeira:
Educational Data Mining: Analysis of Drop out of Engineering Majors at the UnB - Brazil. 259-262 - Mauricio Barros de Jesus, Gladston Luiz da Silva, Marcelo Ladeira, Gustavo Cordeiro Galvão Van Erven:
Using Text Mining to Categorize the Purpose of Public Spending for the Benefit of Transparency and Accountability. 263-267 - Houtao Deng, Ganesh Krishnan, Ji Chen, Dong Liang:
Leveraging Elastic Demand for Forecasting. 268-271 - Duy Hoang Thai, Hau-Tieng Wu, David B. Dunson:
Locally Convex Kernel Mixtures: Bayesian Subspace Learning. 272-275 - Henry Kvinge, Elin Farnell, Jingya Li, Yujia Chen:
Rare Geometries: Revealing Rare Categories via Dimension-Driven Statistics. 276-281 - Ricardo Filipe, Filipe Araújo:
Client-Side Monitoring of HTTP Clusters Using Machine Learning Techniques. 282-286 - Jingyi Shen, M. Omair Shafiq:
Learning Mobile Application Usage - A Deep Learning Approach. 287-292 - Finn Kuusisto, Vítor Santos Costa, Zhonggang Hou, James A. Thomson, David Page, Ron M. Stewart:
Machine Learning to Predict Developmental Neurotoxicity with High-Throughput Data from 2D Bio-Engineered Tissues. 293-298 - Meiyan Xie, Yunzhe Xue, Usman Roshan:
Stochastic Coordinate Descent for 01 Loss and Its Sensitivity to Adversarial Attacks. 299-304 - Sabine Apfeld, Alexander Charlish, Gerd Ascheid:
Modelling, Learning and Prediction of Complex Radar Emitter Behaviour. 305-310 - David Haley, Ehsan Kamalinejad, Jiaofei Zhong:
IsoClustering: A Generalized Framework for Local Data Clustering. 311-314 - Shokoufeh Monjezi Kouchak, Ashraf Gaffar:
Using Bidirectional Long Short Term Memory with Attention Layer to Estimate Driver Behavior. 315-320 - Ahmed Lasisi, Mufutau Obanishola Sadiq, Ibrahim Balogun, Abdulfatai Tunde-Lawal, Nii O. Attoh-Okine:
A Boosted Tree Machine Learning Alternative to Predictive Evaluation of Nondestructive Concrete Compressive Strength. 321-324 - Fereshteh Jafariakinabad, Kien A. Hua:
Style-Aware Neural Model with Application in Authorship Attribution. 325-328 - Laura Dörr, Felix Brandt, Anne Meyer, Martin Pouls:
Lean Training Data Generation for Planar Object Detection Models in Unsteady Logistics Contexts. 329-334 - Reinaldo Sanchez-Arias, Roberto Williams Batista:
Unsupervised Learning on the Health and Retirement Study using Geometric Data Analysis. 335-340 - Anastasia Gaydashenko, Sangeeta Ramakrishnan:
A Machine Learning Approach to Maximizing Broadband Capacity via Dynamic DOCSIS 3.1 Profile Management. 341-345 - Sunil Bharitkar:
Encoding in Neural Networks. 346-351 - Dominic Henze, Klaidi Gorishti, Bernd Bruegge, Jan-Philipp Simen:
AudioForesight: A Process Model for Audio Predictive Maintenance in Industrial Environments. 352-357 - Felix Wick, Ulrich Kerzel, Michael Feindt:
Cyclic Boosting - An Explainable Supervised Machine Learning Algorithm. 358-363 - Amal AlQahtani, Efsun Sarioglu Kayi, Mona T. Diab:
Understanding Cohesion in Writings and Speech of Schizophrenia Patients. 364-369 - Niklas Karvonen, Joakim Nilsson, Denis Kleyko, Lara Lorna Jiménez:
Low-Power Classification using FPGA - An Approach based on Cellular Automata, Neural Networks, and Hyperdimensional Computing. 370-375 - Yosef Ashibani, Qusay H. Mahmoud:
Classification and Feature Extraction for User Identification for Smart Home Networks Based on Apps Access History. 376-380 - Karsten Maurer, Walter D. Bennette:
Facility Locations Utility for Uncovering Classifier Overconfidence. 381-386 - Igor Khokhlov, Leon Reznik, Rohit Bhaskar:
The Machine Learning Models for Activity Recognition Applications with Wearable Sensors. 387-391 - Durdane Kocacoban, James Cussens:
Online Causal Structure Learning in the Presence of Latent Variables. 392-395 - Nelly Elsayed, Anthony S. Maida, Magdy A. Bayoumi:
An Analysis of Univariate and Multivariate Electrocardiography Signal Classification. 396-399 - Manuel Alberto Cordova Neira, Luis G. L. Decker, Jose L. Flores-Campana, Andreza A. dos Santos, Jhonatas S. Conceição, Allan da Silva Pinto, Hélio Pedrini, Ricardo da Silva Torres:
Pelee-Text: A Tiny Convolutional Neural Network for Multi-oriented Scene Text Detection. 400-405 - Sanket Shukla, Gaurav Kolhe, Sai Manoj P. D., Setareh Rafatirad:
RNN-Based Classifier to Detect Stealthy Malware using Localized Features and Complex Symbolic Sequence. 406-409 - Pritam Sarkar, Vandad Davoodnia, Ali Etemad:
Computer-Aided Diagnosis using Class-Weighted Deep Neural Network. 410-413 - Ken-ichi Fukui, Junya Tanaka, Tomohiko Tomita, Masayuki Numao:
Physics-Guided Neural Network with Model Discrepancy Based on Upper Troposphere Wind Prediction. 414-419 - Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akcay, Toby P. Breckon:
Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery. 420-425 - Michael Woodham, Jason Hawkins, Ankita Singh, Shayok Chakraborty:
When to Pull Starting Pitchers in Major League Baseball? A Data Mining Approach. 426-431 - Gadiel Sznaier Camps, Nicolas Bohm Agostini, David R. Kaeli:
Discovering Programmer Intention Behind Written Source Code. 432-437 - Kazem Qazanfari, Abdou Youssef:
Word Embedding by Combining Resources and Integrating Techniques. 438-443 - Macilio da Silva Ferreira, Lucio Flavio Vismari, Paulo Sérgio Cugnasca, Jorge Rady de Almeida Jr., João Batista Camargo Jr., Guilherme Kallemback:
A Comparative Analysis of Unsupervised Learning Techniques for Anomaly Detection in Railway Systems. 444-449 - Yesmina Jaâfra, Aline Deruyver, Jean Luc Laurent, Mohamed Saber Naceur:
Context-Aware Autonomous Driving Using Meta-Reinforcement Learning. 450-455 - Marmar Orooji, Jianhua Chen:
Predicting Louisiana Public High School Dropout through Imbalanced Learning Techniques. 456-461 - Cedric Oeldorf, Gerasimos Spanakis:
LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks. 462-468 - Eduardo A. Soares, Plamen P. Angelov, Dimitar P. Filev, Bruno Costa, Marcos Castro, Subramanya Nageshrao:
Explainable Density-Based Approach for Self-Driving Actions Classification. 469-474 - Safura Sharifi, Sofia Brown, Irina Novikova, Eugeniy E. Mikhailov, Georgios Veronis, Jonathan Dowling, Yaser Banadaki, Elisha Siddiqui, Savannah Cuzzo, Narayan Bhusal, Lior Cohen, Austin Kalasky, Nik Prajapati, Rachel Soto-Garcia:
Identifying Laguerre-Gaussian Modes using Convolutional Neural Network. 475-478 - Anirudh Muthukumar, Ramakrishnan Durairajan:
Denoising Internet Delay Measurements using Weak Supervision. 479-484 - Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Ashwin Shashidharan, Benjamin Dutton, Ranga Raju Vatsavai:
Scalable Data Parallel Approaches to Anomaly Detection in Climate Data using Gaussian Processes. 485-488 - Kyle A. Caudle, Randy C. Hoover, Aaron Alphonsus, Shashwati Shradha:
Advanced Decision Making and Interpretability through Neural Shrubs. 489-494 - Philip A. Adey, Oliver K. Hamilton, Magnus Bordewich, Toby P. Breckon:
Region Based Anomaly Detection with Real-Time Training and Analysis. 495-499 - Stephen Wooley, Andrew Edmonds, Arunkumar Bagavathi, Siddharth Krishnan:
Extracting Cryptocurrency Price Movements from the Reddit Network Sentiment. 500-505 - Xiaofeng Zhu, Feng Liu, Goce Trajcevski, Dingding Wang:
Frosting Weights for Better Continual Training. 506-510 - Revanth Akella, Teng-Sheng Moh:
Mood Classification with Lyrics and ConvNets. 511-514 - Richard V. R. Mariano, Geanderson E. dos Santos, Markos V. de Almeida, Wladmir C. Brandão:
Feature Changes in Source Code for Commit Classification Into Maintenance Activities. 515-518 - Sheng Huang, Zheng Hua Shi:
An Application of Autonomous Learning Multimodel System for Localization in Industrial Warehouse Storage Rack. 519-522 - Sayan Chakraborty, Smit Shah, Kiumars Soltani, Anna Swigart:
Root Cause Detection Among Anomalous Time Series Using Temporal State Alignment. 523-528 - Zilong Jiao, Jae C. Oh:
Asynchronous Multitask Reinforcement Learning with Dropout for Continuous Control. 529-534 - Zilong Jiao, Jae C. Oh:
End-to-End Reinforcement Learning for Multi-agent Continuous Control. 535-540 - Gaddiel Desirena, Armando Diaz, Jalil Desirena, Ismael Moreno, Daniel Garcia:
Maximizing Customer Lifetime Value using Stacked Neural Networks: An Insurance Industry Application. 541-544 - Fei Gao, Jiangjiang Liu:
Face Recognition Using Segmentation Technology. 545-548 - Jose Mijangos, Glenn Bruns:
Assessing Wireless Data Services with Machine Learning and Geostatistics. 549-554 - Alvi Md. Ishmam, Sadia Sharmin:
Hateful Speech Detection in Public Facebook Pages for the Bengali Language. 555-560 - Mohsin Munir, Muhammad Ali Chattha, Andreas Dengel, Sheraz Ahmed:
A Comparative Analysis of Traditional and Deep Learning-Based Anomaly Detection Methods for Streaming Data. 561-566
Session 10: Machine Learning Algorithms (I)
- Nicolas Knudde, Ivo Couckuyt, Kohei Shintani, Tom Dhaene:
Active Learning for Feasible Region Discovery. 567-572 - Ze Jin, David S. Matteson, Tianrong Zhang:
Independent Component Analysis Based on Mutual Dependence Measures. 573-580 - Ramin Nikzad-Langerodi, Werner Zellinger, Susanne Saminger-Platz, Bernhard Moser:
Domain-Invariant Regression Under Beer-Lambert's Law. 581-586 - Xiang Liu, Ziyang Tang, Huyunting Huang, Tonglin Zhang, Baijian Yang:
Multiple Learning for Regression in Big Data. 587-594 - Ryoya Yamasaki, Toshiyuki Tanaka:
Kernel Selection for Modal Linear Regression: Optimal Kernel and IRLS Algorithm. 595-601
Session 11: Deep Learning Applications
- Daniel Gutiérrez, Sergio Toral:
Deep Neuronal Based Classifiers for Wireless Multi-hop Network Mobility Models. 602-607 - Girish J. Showkatramani, Nidhi Khatri, Arlene Landicho, Darwin Layog:
Deep Learning Approach to Trademark International Class Identification. 608-612 - Russell Sabir, Daniele Rosato, Sven Hartmann, Clemens Gühmann:
LSTM Based Bearing Fault Diagnosis of Electrical Machines using Motor Current Signal. 613-618 - Shantanu Deshmukh, Philip Heller, Natalia Khuri:
A Long-Short Term Memory Network for Detecting CRISPR Arrays. 619-624
Session 12: Object Detection
- Chang Liu, Xizhe Wang, Jing Ni, Yu Cao, Benyuan Liu:
An Edge Computing Visual System for Vegetable Categorization. 625-632 - Thiago D'Angelo, Marina Mendes, Breno N. S. Keller, Rafael Ferreira, Saul E. Delabrida, Ricardo Augusto Rabelo Oliveira, Héctor Azpúrua, Andrea G. C. Bianchi:
Deep Learning-Based Object Detection for Digital Inspection in the Mining Industry. 633-640 - Khalid N. Ismail, Toby P. Breckon:
On the Performance of Extended Real-Time Object Detection and Attribute Estimation within Urban Scene Understanding. 641-646 - Nithesh Singh Sanjay, Ali Ahmadinia:
MobileNet-Tiny: A Deep Neural Network-Based Real-Time Object Detection for Rasberry Pi. 647-652 - Ganesh Samarth C. A., Neelanjan Bhowmik, Toby P. Breckon:
Experimental Exploration of Compact Convolutional Neural Network Architectures for Non-Temporal Real-Time Fire Detection. 653-658
Session 13: Text Mining
- Omid Shahmirzadi, Adam Lugowski, Kenneth Younge:
Text Similarity in Vector Space Models: A Comparative Study. 659-666 - Feng Liu, Liangji Wang, Xiaofeng Zhu, Dingding Wang:
Suggestion Mining from Online Reviews usingRandom Multimodel Deep Learning. 667-672 - Swarup Ranjan Behera, Parag Agrawal, Amit Awekar, Vijaya Saradhi Vedula:
Mining Strengths and Weaknesses of Cricket Players Using Short Text Commentary. 673-679 - Daniel de Souza Costa Pedroso, Marcelo Ladeira, Thiago de Paulo Faleiros:
Does Semantic Search Performs Better than Lexical Search in the Task of Assisting Legal Opinion Writing? 680-685
Session 14: Deep Learning Algorithms (II)
- Chang Song, Zuoguan Wang, Hai Li:
Feedback Learning for Improving the Robustness of Neural Networks. 686-693 - Javier Antorán, Antonio Miguel:
Disentangling and Learning Robust Representations with Natural Clustering. 694-699 - Nadia Burkart, Marco F. Huber, Phillip Faller:
Forcing Interpretability for Deep Neural Networks through Rule-Based Regularization. 700-705 - Yuriy Mishchenko, Yusuf Goren, Ming Sun, Chris Beauchene, Spyros Matsoukas, Oleg Rybakov, Shiv Naga Prasad Vitaladevuni:
Low-Bit Quantization and Quantization-Aware Training for Small-Footprint Keyword Spotting. 706-711
Session 15: Social Networks and Event Mining
- Yao Zhang, Changwei Hu, Yifan Hu, Tejaswi Kasturi, Shanmugam Ramasamy, Matt Gillingham, Keith Yamamoto:
Large-Scale Gender/Age Prediction of Tumblr Users. 712-717 - Scott Wahl, John Sheppard, Elizabeth Shanahan:
Legislative Vote Prediction using Campaign Donations and Fuzzy Hierarchical Communities. 718-725 - Qiyao Wang, Ahmed K. Farahat, Kosta Ristovski, Chetan Gupta, Shuai Zheng:
Evaluation of Event Impact on Key Performance Indicators. 726-733 - Debanjana Banerjee, Ritish Menon:
Complete Rare Event Specification using Stochastic Treatment: CRESST. 734-739
Session 16: Machine Learning on Imbalanced Data
- Marlu da Silva Santos, Marcelo Ladeira, Gustavo Cordeiro Galvão Van Erven, Gladston Luiz da Silva:
Machine Learning Models to Identify the Risk of Modern Slavery in Brazilian Cities. 740-746 - Leopoldo Soares de Melo Junior, Franco Maria Nardini, Chiara Renso, José Antônio Fernandes de Macêdo:
An Empirical Comparison of Classification Algorithms for Imbalanced Credit Scoring Datasets. 747-754 - Justin M. Johnson, Taghi M. Khoshgoftaar:
Deep Learning and Thresholding with Class-Imbalanced Big Data. 755-762 - Aaron N. Richter, Taghi M. Khoshgoftaar:
Learning Curve Estimation with Large Imbalanced Datasets. 763-768
Session 17: Deep Learning Algorithms (III)
- Mehdi Jafarnia-Jahromi, Tasmin Chowdhury, Hsin-Tai Wu, Sayandev Mukherjee:
PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning. 769-776 - Abdullah-Al-Zubaer Imran, Demetri Terzopoulos:
Multi-adversarial Variational Autoencoder Networks. 777-782 - Alexey Malistov, Arseniy Trushin:
Gradient Boosted Trees with Extrapolation. 783-789 - Qing Yang, Wei Wen, Zuoguan Wang, Hai Li:
Joint Regularization on Activations and Weights for Efficient Neural Network Pruning. 790-797
Session 18: Natural Language Processing
- Jacob Krantz, Maxwell Dulin, Paul De Palma:
Language-Agnostic Syllabification with Neural Sequence Labeling. 804-810 - Sawsan Alqahtani, Mona T. Diab:
Investigating Input and Output Units in Diacritic Restoration. 811-817
Session 19: Machine Learning for Self Driving
- Keuntaek Lee, Ziyi Wang, Bogdan I. Vlahov, Harleen K. Brar, Evangelos A. Theodorou:
Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies. 831-837 - Daichi Murata, Toru Motoya, Hiroaki Ito:
Automatic CNN Compression System for Autonomous Driving. 838-843 - Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng:
Discretionary Lane Change Decision Making using Reinforcement Learning with Model-Based Exploration. 844-850 - Xinzi Sun, Pengfei Zhang, Dechun Wang, Yu Cao, Benyuan Liu:
Colorectal Polyp Segmentation by U-Net with Dilation Convolution. 851-858
Session 20: Machine Learning on Acoustic Data
- Carlos Vicente Soares Araujo, Marco Antônio Pinheiro de Cristo, Rafael Giusti:
Predicting Music Popularity Using Music Charts. 859-864 - Hamed Mohebbi-Kalkhoran, Chenyang Zhu, Matthew Schinault, Purnima Ratilal:
Classifying Humpback Whale Calls to Song and Non-Song Vocalizations using Bag of Words Descriptor on Acoustic Data. 865-870 - Truc Nguyen, Alexander Fuchs, Franz Pernkopf:
Acoustic Scene Classification Using Deep Mixtures of Pre-trained Convolutional Neural Networks. 871-875
Session 21: Machine Learning Applications
- Indu John, Ravikumar Karumanchi, Shalabh Bhatnagar:
Predictive and Prescriptive Analytics for Performance Optimization: Framework and a Case Study on a Large-Scale Enterprise System. 876-881 - Jivitesh Sharma, Bernt Viggo Matheussen, Sondre Glimsdal, Ole-Christoffer Granmo:
Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms. 882-888 - Cícero Augusto de Lara Pahins, Fabrício D'Morison, Thiago M. Rocha, Larissa M. Almeida, Arthur F. Batista, Diego F. Souza:
T-REC: Towards Accurate Bug Triage for Technical Groups. 889-895
Session 22: Machine Learning Algorithms (II)
- Akhil Mathur, Anton Isopoussu, Fahim Kawsar, Nadia Bianchi-Berthouze, Nicholas D. Lane:
FlexAdapt: Flexible Cycle-Consistent Adversarial Domain Adaptation. 896-901 - Jayaraman J. Thiagarajan, Satyananda Kashyap, Alexandros Karargyris:
Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation. 902-907 - Robert Smith, Jebediah Rosen, Dan Ventura:
Adapting Standard External Clustering Metrics for Repetitive, Noisy Observations. 908-914 - Kevin Alexander Laube, Andreas Zell:
Prune and Replace NAS. 915-921 - Marnick Vanloffelt, Gonzalo Nápoles, Koen Vanhoof:
Fuzzy-Rough Cognitive Networks: Building Blocks and Their Contribution to Performance. 922-928 - Nikki Lijing Kuang, Clement H. C. Leung:
Performance Effectiveness of Multimedia Information Search Using the Epsilon-Greedy Algorithm. 929-936 - Christopher A. Choquette-Choo, David Sheldon, Jonny Proppe, John Alphonso-Gibbs, Harsha Gupta:
A Multi-label, Dual-Output Deep Neural Network for Automated Bug Triaging. 937-944
Session 23: Machine Learning on Healthcare and Medical Data
- Sadaf Kabir, Leily Farrokhvar:
Non-Linear Feature Selection for Prediction of Hospital Length of Stay. 945-950 - Mohammed Bany Muhammad, Ashraf Moinuddin, Ming Ta Michael Lee, Yanfei Zhang, Vida Abedi, Ramin Zand, Mohammed Yeasin:
Deep Ensemble Network for Quantification and Severity Assessment of Knee Osteoarthritis. 951-957 - Sharif Amit Kamran, Sourajit Saha, Ali Shihab Sabbir, Alireza Tavakkoli:
Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images. 964-971
Session 24: Anomaly Detection
- Taesik Gong, Alberto Gil C. P. Ramos, Sourav Bhattacharya, Akhil Mathur, Fahim Kawsar:
AudiDoS: Real-Time Denial-of-Service Adversarial Attacks on Deep Audio Models. 978-985 - Neelanjan Bhowmik, Yona Falinie A. Gaus, Samet Akçay, Jack W. Barker, Toby P. Breckon:
On the Impact of Object and Sub-Component Level Segmentation Strategies for Supervised Anomaly Detection within X-Ray Security Imagery. 986-991 - Okwudili M. Ezeme, Qusay H. Mahmoud, Akramul Azim:
A Deep Learning Approach to Distributed Anomaly Detection for Edge Computing. 992-999 - Iman Vasheghani Farahani, Alex Chien, Russell E. King, Michael G. Kay, Brad Klenz:
Time Series Anomaly Detection from a Markov Chain Perspective. 1000-1007 - Yingshui Tan, Baihong Jin, Alexander J. Nettekoven, Yuxin Chen, Yisong Yue, Ufuk Topcu, Alberto L. Sangiovanni-Vincentelli:
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. 1008-1015 - David F. N. Oliveira, Marcelo M. Neves, Lucio Flavio Vismari, Jorge Rady de Almeida Jr., Paulo Sérgio Cugnasca, João Batista Camargo Jr., Eduardo M. G. Rodrigues, Debora R. Doimo, Leandro P. F. de Almeida, Rafael Gripp:
Evaluating Unsupervised Anomaly Detection Models to Detect Faults in Heavy Haul Railway Operations. 1016-1022 - Kiyoshi Nakayama, Nikhil Muralidhar, Chenrui Jin, Ratnesh Sharma:
Detection of False Data Injection Attacks in Cyber-Physical Systems using Dynamic Invariants. 1023-1030
Special Session Presentations
Session 1: Predictive Models in Engineering Applications I
- Mingon Kang, Ashis Kumer Biswas, Dong-Chul Kim, Jean Gao:
Semi-Supervised Discriminative Transfer Learning in Cross-Language Text Classification. 1031-1038 - Xiaotao Li, Shujuan You, Wai Chen:
Inducing Embeddings for Rare Words through Morphological Decomposition, Stemming and Bidirectional Translation. 1039-1044 - Huanjing Wang, Taghi M. Khoshgoftaar:
A Study on Software Metric Selection for Software Fault Prediction. 1045-1050 - Jiangning Chen, Zhibo Dai, Juntao Duan, Heinrich Matzinger, Ionel Popescu:
Naive Bayes with Correlation Factor for Text Classification Problem. 1051-1056 - Samira Soleimani, Ali Mohammadi, Jianhua Chen, Michael Leitner:
Mining the Highway-Rail Grade Crossing Crash Data: A Text Mining Approach. 1063-1068
Session 2: Topological Data Analysis in Machine Learning I
- Rickard Brüel Gabrielsson, Gunnar E. Carlsson:
Exposition and Interpretation of the Topology of Neural Networks. 1069-1076 - Samir Chowdhury, Thomas Gebhart, Steve Huntsman, Matvey Yutin:
Path Homologies of Deep Feedforward Networks. 1077-1082 - Stefania Ebli, Gard Spreemann:
A Notion of Harmonic Clustering in Simplicial Complexes. 1083-1090 - Joshua L. Mike, Jose Perea:
Multiscale Geometric Data Analysis via Laplacian Eigenvector Cascading. 1091-1098 - Jacek Cyranka, Alexander Georges, David Meyer:
Mapper Based Classifier. 1099-1106 - Francis C. Motta, John Harer, Nick Leiby, Franco Marinozzi, Scott Novotney, Gabe Rocklin, Jed Singer, Devin Strickland, Matt Vaughn, Christopher J. Tralie, Rossella Bedini, Fabiano Bini, Gilberto Bini, Hamed Eramian, Marcio Gameiro, Steven B. Haase, Hugh Haddox:
Hyperparameter Optimization of Topological Features for Machine Learning Applications. 1107-1114 - Luis Polanco, Jose A. Perea:
Adaptive Template Systems: Data-Driven Feature Selection for Learning with Persistence Diagrams. 1115-1121
Session 3: Machine and Deep Learning in Cybersecurity and Privacy Issues I
- Deepthi Hassan Lakshminarayana, James Philips, Nasseh Tabrizi:
A Survey of Intrusion Detection Techniques. 1122-1129 - Khandaker Abir Rahman, Deepak Neupane, Abdulrahman Zaiter, Md. Shafaeat Hossain:
Web User Authentication Using Chosen Word Keystroke Dynamics. 1130-1135 - Jonathan Villain, Anthony Fleury, Virginie Deniau, Christophe Gransart, Eric Pierre Simon:
Online EM Monitoring of 802.11n Networks using Self Adaptive Kernel Machine. 1136-1142 - Sunguk Shin, Inseop Lee, Changhee Choi:
Anomaly Dataset Augmentation Using the Sequence Generative Models. 1143-1148 - Baik Dowoo, Yujin Jung, Changhee Choi:
PcapGAN: Packet Capture File Generator by Style-Based Generative Adversarial Networks. 1149-1154 - Heemany Shekhar, Melody Moh, Teng-Sheng Moh:
Exploring Adversaries to Defend Audio CAPTCHA. 1155-1161 - Sven Nomm, Alejandro Guerra-Manzanares, Hayretdin Bahsi:
Towards the Integration of a Post-Hoc Interpretation Step into the Machine Learning Workflow for IoT Botnet Detection. 1162-1169
Session 4: Predictive Models in Engineering Applications II
- Cristian Axenie, Radu Tudoran, Stefano Bortoli, Mohamad Al Hajj Hassan, Carlos Salort Sánchez, Goetz Brasche:
Dimensionality Reduction for Low-Latency High-Throughput Fraud Detection on Datastreams. 1170-1177 - Salim Moudache, Mourad Badri:
Software Fault Prediction Based on Fault Probability and Impact. 1178-1185 - Ashkan Ebadi, Yvan Gauthier, Stéphane Tremblay, Patrick Paul:
How can Automated Machine Learning Help Business Data Science Teams? 1186-1191 - Ryuichi Ueno, Robert M. Bryce, Dragos Calitoiu:
Ranking Clusters of Postal Codes to Improve Recruitment in the Canadian Armed Forces. 1192-1197 - Fahad Alhasoun, Marta C. González:
Urban Street Contexts Classification Using Convolutional Neural Networks and Streets Imagery. 1198-1204 - Klára Pesková, Roman Neruda:
Hyperparameters Search Methods for Machine Learning Linear Workflows. 1205-1210
Session 5: Topological Data Analysis in Machine Learning II
- Melih C. Yesilli, Sarah Tymochko, Firas A. Khasawneh, Elizabeth Munch:
Chatter Diagnosis in Milling Using Supervised Learning and Topological Features Vector. 1211-1218 - Noah Giansiracusa, Robert Giansiracusa, Chul Moon:
Persistent Homology Machine Learning for Fingerprint Classification. 1219-1226 - Sarah Tymochko, Elizabeth Munch, Firas A. Khasawneh:
Adaptive Partitioning for Template Functions on Persistence Diagrams. 1227-1234 - Paul Samuel Ignacio, Christopher Dunstan, Esteban Escobar, Luke Trujillo, David Uminsky:
Classification of Single-Lead Electrocardiograms: TDA Informed Machine Learning. 1241-1246 - Farzana Nasrin, Christopher Oballe, David L. Boothe, Vasileios Maroulas:
Bayesian Topological Learning for Brain State Classification. 1247-1252
Session 6: Machine and Deep Learning in Cybersecurity and Privacy Issues
- Petros Toupas, Dimitra Chamou, Konstantinos M. Giannoutakis, Anastasios Drosou, Dimitrios Tzovaras:
An Intrusion Detection System for Multi-class Classification Based on Deep Neural Networks. 1253-1258 - Rasana Manandhar, Shaya Wolf, Mike Borowczak:
One-Class Classification to Continuously Authenticate Users Based on Keystroke Timing Dynamics. 1259-1266 - Andrew Walker, Joydeep Acharya:
Data Integrity of Industrial Controllers via Multi-resolution Hierarchical Time Series Clustering. 1267-1274 - Daniel Park, Haidar Khan, Bülent Yener:
Generation & Evaluation of Adversarial Examples for Malware Obfuscation. 1283-1290 - Watson Jia, Raj Mani Shukla, Shamik Sengupta:
Anomaly Detection using Supervised Learning and Multiple Statistical Methods. 1291-1297 - Mayra Alexandra Macas Carrasco, Chunming Wu:
An Unsupervised Framework for Anomaly Detection in a Water Treatment System. 1298-1305
Session 7: Machine and Deep Learning in Cybersecurity and Privacy Issues
- Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts. 1306-1313 - Graham White, Daniel Cunnington, Mark Law, Elisa Bertino, Geeth de Mel, Alessandra Russo:
A Comparison Between Statistical and Symbolic Learning Approaches for Generative Policy Models. 1314-1321 - Maxwell Berman, Stephen C. Adams, Tim Sherburne, Cody H. Fleming, Peter A. Beling:
Active Learning to Improve Static Analysis. 1322-1327 - Igor Khokhlov, Michael Perez, Leon Reznik:
Machine Learning in Anomaly Detection: Example of Colluded Applications Attack in Android Devices. 1328-1333 - Steven Yen, Melody Moh, Teng-Sheng Moh:
CausalConvLSTM: Semi-Supervised Log Anomaly Detection Through Sequence Modeling. 1334-1341
Special Session Posters
Special Session: Machine Learning in Advanced Machine Vision
- Albert Bruce Chu, Maxwell Murialdo, James P. Lewicki, Jennifer N. Rodriguez, Mitchell K. Shiflett, Brian Giera, Alan David Kaplan:
Image Classification of Clogs in Direct Ink Write Additive Manufacturing. 1342-1347
Special Session: Deep Learning
- W. Graham Mueller, Alex Memory, Kyle Bartrem:
Causal Discovery of Cyber Attack Phases. 1348-1352 - Xian Wang, Lingqiao Liu, Qinfeng Shi:
Exploiting Stereo Sound Channels to Boost Performance of Neural Network-Based Music Transcription. 1353-1358 - Elham Khorasani Buxton, Kenneth Kriz, Matthew Cremeens, Kim Jay:
An Auto Regressive Deep Learning Model for Sales Tax Forecasting from Multiple Short Time Series. 1359-1364 - Ajay Shrestha, Ausif Mahmood:
Optimizing Deep Neural Network Architecture with Enhanced Genetic Algorithm. 1365-1370 - Abdullah Almutairi, Meshal Alfarhood:
Instance Segmentation of Newspaper Elements Using Mask R-CNN. 1371-1375 - Ziqiang Shi, Chaoliang Zhong, Yasuto Yokota, Wensheng Xia, Jun Sun:
Robustness Evaluation of Deep Learning Models Based on Local Prediction Consistency. 1376-1381 - Siva Skandha Sanagala, Suneet K. Gupta, Vijaya Kumar Koppula, Mohit Agarwal:
A Fast and Light Weight Deep Convolution Neural Network Model for Cancer Disease Identification in Human Lung(s). 1382-1387 - Duc Hoang, Jesse Hamer, Gabriel N. Perdue, Steven R. Young, Jonathan A. Miller, Anushree Ghosh:
Inferring Convolutional Neural Networks' Accuracies from Their Architectural Characterizations. 1388-1391 - Charalampos Karyotis, Tomasz Maniak, Faiyaz Doctor, Rahat Iqbal, Vasile Palade, Raymond Tang:
Deep Learning for Flood Forecasting and Monitoring in Urban Environments. 1392-1397 - Jingjing Wang, Fei Song, Kavita Walia, Jeffery Farber, Rozita A. Dara:
Using Convolutional Neural Networks to Extract Keywords and Keyphrases: A Case Study for Foodborne Illnesses. 1398-1403 - Elijah Bolluyt, Cristina Comaniciu:
Collapse Resistant Deep Convolutional GAN for Multi-object Image Generation. 1404-1408 - Souvik Hazra, Avik Santra:
Radar Gesture Recognition System in Presence of Interference using Self-Attention Neural Network. 1409-1414 - Sharada Murali, Mohammad Reza Rajati, Somasekhar Suryadevara:
Image Generation and Style Transfer Using Conditional Generative Adversarial Networks. 1415-1419 - Hossein Hassani, Maryam Farajzadeh-Zanjani, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade:
Design of a Cost-Effective Deep Convolutional Neural Network-Based Scheme for Diagnosing Faults in Smart Grids. 1420-1425
Special Session: Machine Learning in Health
- Sindhura Bonthu, Priscila Rodrigues Armijo, Tiffany Tanner, Qiuming Zhu:
Using Machine Learning to Improve Surgical Outcomes. 1426-1431 - Nader Naghavi, Soheil Borhani, Eric Wade:
Improving Machine Learning Based Detection of Freezing of Gait Using Data Synthesis Methods. 1432-1437 - Xueqin Pang, Christopher B. Forrest, Félice Lê-Scherban, Aaron J. Masino:
Understanding Early Childhood Obesity via Interpretation of Machine Learning Model Predictions. 1438-1443 - Tejul Pandit, Harshal Nahane, Dhanshree Lade, Vaibhav Rao:
Abnormal Gait Detection by Classifying Inertial Sensor Data using Transfer Learning. 1444-1447 - Matthew Wai Heng Chung, Jianyu Liu, Hegler Tissot:
Clinical Knowledge Graph Embedding Representation Bridging the Gap between Electronic Health Records and Prediction Models. 1448-1453 - Ákos Rudas, Sándor Laki:
On Activity Identification Pipelines for a Low-Accuracy EEG Device. 1454-1459 - Rosemarie J. Day, Hassan Salehi, Mahsa Javadi:
IoT Environmental Analyzer using Sensors and Machine Learning for Migraine Occurrence Prevention. 1460-1465 - Hanieh Marvi-Khorasani, Hamid Usefi:
Feature Clustering Towards Gene Selection. 1466-1469 - Renata C. Santana, Bruno César dos Santos, Thiago H. N. de Lima, Maycoln L. M. Teodoro, Saulo Pinto, Luiz Zárate, Cristiane Nobre:
Genetic Algorithms for Feature Selection in the Children and Adolescents Depression Context. 1470-1475
Special Session: Machine Learning for Predictive Models in Engineering Applications
- S. M. Shafiul Hasan, Masudur R. Siddiquee, Ou Bai:
Supervised Classification of EEG Signals with Score Threshold Regulation for Pseudo-Online Asynchronous Detection of Gait Intention. 1476-1479 - Carlos Salort Sánchez, Radu Tudoran, Mohamad Al Hajj Hassan, Stefano Bortoli, Goetz Brasche, Jan Baumbach, Cristian Axenie:
An Online Incremental Clustering Framework for Real-Time Stream Analytics. 1480-1485 - Ramakrishna Valisetty:
Machine Learning of the Ultrasound Signal Travel Path Effect in Estimating the Residual Life of the US Army Vehicles. 1486-1491 - Adithi D. Chakravarthy, Sindhura Bonthu, Zhengxin Chen, Qiuming Zhu:
Predictive Models with Resampling: A Comparative Study of Machine Learning Algorithms and their Performances on Handling Imbalanced Datasets. 1492-1495 - Achille Salaün, Yohan Petetin, François Desbouvries:
Comparing the Modeling Powers of RNN and HMM. 1496-1499 - Kittichai Lavangnananda, Peerasak Wangsom:
Multi-objective Shipment Allocation using Extreme Nondominated Sorting Genetic Algorithm-III (E-NSGA-III). 1500-1505 - Forrest Jehlik, Alvaro Blazquez de Mingo:
A Deep Learning Approach to Modeling a Complex Multi-variate, Temporal Thermal Problem. 1506-1510 - Xuan Liao, Mayank Tyagi:
Predictive Analytics and Statistical Learning for Waterflooding Operations in Reservoir Simulations. 1511-1516 - Arunkumar Bagavathi, Siddharth Krishnan, Sanjay Subrahmanyan, S. L. Narasimhan:
ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert. 1517-1522 - Ha-Ram Won, Yunju Lee, Jae-Seung Shim, Hyunchul Ahn:
A Hybrid Collaborative Filtering Model Using Customer Search Keyword Data for Product Recommendation. 1523-1526 - Truong-Thanh Ma, Salem Benferhat, Zied Bouraoui, Karim Tabia, Thanh-Nghi Do, Nguyen-Khang Pham:
An Automatic Extraction Tool for Ethnic Vietnamese Thai Dances Concepts. 1527-1530
Special Session: Topological Data Analysis in Machine Learning
- Emilie Dufresne, Parker B. Edwards, Heather A. Harrington, Jonathan D. Hauenstein:
Sampling Real Algebraic Varieties for Topological Data Analysis. 1531-1536 - Thomas Gebhart, Paul Schrater, Alan Hylton:
Characterizing the Shape of Activation Space in Deep Neural Networks. 1537-1542 - Michael S. Postol, Candace Diaz, Robert Simon, Drew Wicke:
Time-Series Data Analysis for Classification of Noisy and Incomplete Internet-of-Things Datasets. 1543-1550 - Adélie Garin, Guillaume Tauzin:
A Topological "Reading" Lesson: Classification of MNIST using TDA. 1551-1556 - Mehmet Emin Aktas, Esra Akbas:
Text Classification via Network Topology: A Case Study on the Holy Quran. 1557-1562
Session 8: Machine Learning in Health I
- Akshay Chadha, Rozita Dara, Zvonimir Poljak:
Convolutional Classification of Pathogenicity in H5 Avian Influenza Strains. 1570-1577 - Jing Ni, Qilei Chen, Chang Liu, Honghao Wang, Yu Cao, Benyuan Liu:
An Effective CNN Approach for Diabetic Retinopathy Stage Classification with Dual Inputs and Selective Data Sampling. 1578-1584 - Abhijith Ragav, Nanda Harishankar Krishna, Naveen Narayanan, Kevin Thelly, Vineeth Vijayaraghavan:
Scalable Deep Learning for Stress and Affect Detection on Resource-Constrained Devices. 1585-1592 - Sergey Pavlov, Alexey Artemov, Maksim Sharaev, Alexander Bernstein, Evgeny Burnaev:
Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem. 1600-1605 - Xiaohong W. Gao, Barbara Braden, Stephen Taylor, Wei Pang:
Towards Real-Time Detection of Squamous Pre-Cancers from Oesophageal Endoscopic Videos. 1606-1612
Session 9: Deep Learning I
- Bonifaz Stuhr, Jürgen Brauer:
CSNNs: Unsupervised, Backpropagation-Free Convolutional Neural Networks for Representation Learning. 1613-1620 - Georgios Tzelepis, Ahraz Asif, Saimir Baci, Selcuk Cavdar, Eren Erdal Aksoy:
Deep Neural Network Compression for Image Classification and Object Detection. 1621-1628 - Xiaocong Du, Gouranga Charan, Frank Liu, Yu Cao:
Single-Net Continual Learning with Progressive Segmented Training. 1629-1636 - Harsh Nilesh Pathak, Randy C. Paffenroth:
Parameter Continuation Methods for the Optimization of Deep Neural Networks. 1637-1643 - James Spooner, Madeline Cheah, Vasile Palade, Stratis Kanarachos, Alireza Daneshkhah:
Generation of Pedestrian Pose Structures using Generative Adversarial Networks. 1644-1650 - Adrian Alan Pol, Victor Berger, Cécile Germain, Gianluca Cerminara, Maurizio Pierini:
Anomaly Detection with Conditional Variational Autoencoders. 1651-1657 - Wenjing Li, Randy C. Paffenroth:
Optimal Ensembles for Deep Learning Classification: Theory and Practice. 1658-1665
Session 10: Machine Learning in Energy Application I
- Marc Wenninger, Dominik Stecher, Jochen Schmidt:
SVM-Based Segmentation of Home Appliance Energy Measurements. 1666-1670 - Ömer Ibrahim Erduran, Mirjam Minor, Lars Hedrich, Ahmad Tarraf, Frederik Ruehl, Hans Schroth:
Multi-agent Learning for Energy-Aware Placement of Autonomous Vehicles. 1671-1678 - Valentin Bolz, Johannes Rueß, Andreas Zell:
Power Flow Approximation Based on Graph Convolutional Networks. 1679-1686 - Nikola Markovic, Thomas Stoetzel, Volker Staudt, Dorothea Kolossa:
Hybrid Condition Monitoring for Power Electronic Systems. 1687-1694 - Nathalie Morette, Thierry Ditchi, Yacine Oussar:
Domain Adaptation for Ageing State Recognition of Cables used in Power Systems. 1695-1701 - Hari Prasanna Das, Ioannis C. Konstantakopoulos, Aummul Baneen Manasawala, Tanya Veeravalli, Huihan Liu, Costas J. Spanos:
A Novel Graphical Lasso Based Approach Towards Segmentation Analysis in Energy Game-Theoretic Frameworks. 1702-1709
Session 11: Machine Learning in Health II
- Marina Pominova, Ekaterina Kondrateva, Maksim Sharaev, Alexander Bernstein, Sergey Pavlov, Evgeny Burnaev:
3D Deformable Convolutions for MRI Classification. 1710-1716 - Yogesh Shankar, Souvik Hazra, Avik Santra:
Radar-Based Non-intrusive Fall Motion Recognition using Deformable Convolutional Neural Network. 1717-1724 - Rania Almajalid, Juan Shan, Maolin Zhang, Garrett Stonis, Ming Zhang:
Knee Bone Segmentation on Three-Dimensional MRI. 1725-1730 - Marzieh Mousavian, Jianhua Chen, Steven G. Greening:
Depression Detection Using Feature Extraction and Deep Learning from sMRI Images. 1731-1736 - Siteng Chen, Ao Li, Kathleen Lasick, Julie Huynh, Linda S. Powers, Janet Roveda, Andrew Paek:
Weakly Supervised Deep Learning for Detecting and Counting Dead Cells in Microscopy Images. 1737-1743 - Ghada Zamzmi, Li-Yueh Hsu, Wen Li, Vandana Sachdev, Sameer K. Antani:
Echo Doppler Flow Classification and Goodness Assessment with Convolutional Neural Networks. 1744-1749
Session 12: Deep Learning II
- Anuj Dimri, Suraj Yerramilli, Peng Lee, Sardar Afra, Andrew Jakubowski:
Enhancing Claims Handling Processes with Insurance Based Language Models. 1750-1755 - Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Pattern and Anomaly Localization in Complex and Dynamic Data. 1756-1763 - Andrew W. E. McDonald, Ali Shokoufandeh:
Sparse Super-Regular Networks. 1764-1770 - Lennart Brocki, Neo Christopher Chung:
Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models. 1771-1778 - Matthew L. Weiss, Randy C. Paffenroth, Jacob Whitehill, Joshua R. Uzarski:
Deep Learning with Domain Randomization for Optimal Filtering. 1779-1786 - Sandeep Shivajirao, Rim Hantach, Sarra Ben Abbès, Philippe Calvez:
Mask R-CNN End-to-End Text Detection and Recognition. 1787-1793 - Helena Almeida Maia, Marcos Roberto e Souza, Anderson Santos, Hélio Pedrini, Hemerson Tacon, André de Souza Brito, Hugo de Lima Chaves, Marcelo Bernardes Vieira, Saulo Moraes Villela:
Learnable Visual Rhythms Based on the Stacking of Convolutional Neural Networks for Action Recognition. 1794-1799
Session 13: Predictive Models in Engineering Applications III
- Iuliia Gavriushina, Oliver Sampson, Michael R. Berthold, Winfried Pohlmeier, Christian Borgelt:
Widened Learning of Index Tracking Portfolios. 1800-1805 - Alexandre Moreira Nascimento, Lucio Flavio Vismari, Paulo Sérgio Cugnasca, João Battista Camargo Junior, Jorge Rady de Almeida Júnior:
A Cost-Sensitive Approach to Enhance the use of ML Classifiers in Software Testing Efforts. 1806-1813 - Azim Ahmadzadeh, Berkay Aydin, Dustin J. Kempton, Maxwell Hostetter, Rafal A. Angryk, Manolis K. Georgoulis, Sushant S. Mahajan:
Rare-Event Time Series Prediction: A Case Study of Solar Flare Forecasting. 1814-1820 - Mathieu Jégou, Pierre Chevaillier, Pierre De Loor:
Hierarchical Temporal Memories Prediction Performance and Robustness to Faults on Multivariate Time Series. 1821-1828 - Nasser Assery, Xiaohong Yuan, Sultan Almalki, Kaushik Roy, Xiuli Qu:
Comparing Learning-Based Methods for Identifying Disaster-Related Tweets. 1829-1836 - Yordanka Karayaneva, Sara Sharifzadeh, Yanguo Jing, Kevin Chetty, Bo Tan:
Sparse Feature Extraction for Activity Detection Using Low-Resolution IR Streams. 1837-1843
Session 14: Machine Learning in Health III
- Parminder Bhatia, Busra Celikkaya, Mohammed Khalilia, Selvan Senthivel:
Comprehend Medical: A Named Entity Recognition and Relationship Extraction Web Service. 1844-1851 - Parminder Bhatia, Kristjan Arumae, Busra Celikkaya:
Towards Fast and Unified Transfer Learning Architectures for Sequence Labeling. 1852-1859 - Maria Vaida, Kevin Purcell:
Hypergraph Link Prediction: Learning Drug Interaction Networks Embeddings. 1860-1865
Session 15: Deep Learning III
- Tobias Schlosser, Michael Friedrich, Danny Kowerko:
Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework. 1866-1873 - Sota Yasuda, Shahrzad Mahboubi, S. Indrapriyadarsini, Hiroshi Ninomiya, Hideki Asai:
A Stochastic Variance Reduced Nesterov's Accelerated Quasi-Newton Method. 1874-1879 - Tony Lindsey, Zsolt Garami:
Automated Stenosis Classification of Carotid Artery Sonography using Deep Neural Networks. 1880-1884
Session 16: Predictive Models in Engineering Applications IV
- Sheng Huang, Andri Ashfahani, Mahardhika Pratama:
Wireless Indoor Positioning Using Online Machine Learning. 1885-1890 - Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, Naeem Seliya:
The Effect of Time on the Maintenance of a Predictive Model. 1891-1896 - Gary W. Delaney, David Howard, Krystal De Napoli:
Utilising Evolutionary Algorithms to Design Granular Materials for Industrial Applications. 1897-1902
Session 17: Machine Learning Applications in Education I
- Yo Ehara:
Uncertainty-Aware Personalized Readability Assessments for Second Language Learners. 1909-1916 - Osama Elsarrar, Marjorie Darrah, Richard Devine:
Analysis of Forest Fire Data Using Neural Network Rule Extraction with Human Understandable Rules. 1917-19176 - Kennedy Ralston, Yuhao Chen, Haruna Isah, Farhana H. Zulkernine:
A Voice Interactive Multilingual Student Support System using IBM Watson. 1924-1929
Session 18: Machine Learning in Energy Application II
- Changfu Li, Chenrui Jin, Ratnesh Sharma:
Coordination of PV Smart Inverters Using Deep Reinforcement Learning for Grid Voltage Regulation. 1930-1937 - Neelanjana Pal, Purboday Ghosh, Gabor Karsai:
DeepECO: Applying Deep Learning for Occupancy Detection from Energy Consumption Data. 1938-1943
Session 19: Predictive Models in Engineering Applications V
- Ogechukwu N. Iloanusi, Charles Chukwuma Mbah:
Gender Estimation from a Hybrid of Face, Upper and Full Body Images at Varying Body Poses. 1944-1949 - Fabian Fallas-Moya, Manfred Gonzalez-Hernandez, Luis Barboza-Barquero, Kenneth Obando, Ovidio Valerio, Andrea Holst, Ronald Arias:
Looking for the Best Fit of a Function over Circadian Rhythm Data. 1950-1955 - Rusheng Zhang, Romain Leteurtre, Benjamin Striner, Ammar Alanazi, Abdullah Alghafis, Ozan K. Tonguz:
Partially Detected Intelligent Traffic Signal Control: Environmental Adaptation. 1956-1960
Session 20: Machine Learning Application in Education II
- Kayleigh Hyde, Amy-Jane Griffiths, Cristina Giannantonio, Amy Hurley-Hanson, Sneha Mathur, Erik Linstead:
Exploring the Landscape of Employers for Individuals with Autism Spectrum Disorder. 1961-1967 - Mark Boger, Antonio Laverghetta, Nikolai Fetisov, John Licato:
Generating Near and Far Analogies for Educational Applications: Progress and Challenges. 1968-1975 - Mahmut Coskun, Halil-Ibrahim Bülbül:
Investigation of Factors Affecting Ownership the Household Informatics Equipment with CHAID Algorithm. 1976-1981 - Yo Ehara:
Graph-Based Analysis of Similarities between Word Frequency Distributions of Various Corpora for Complex Word Identification. 1982-1986
Session 21: Machine Learning in Advanced Machine Vision
- Muhammad K. A. Hamdan, Diane T. Rover, Matthew J. Darr, John Just:
Mass Estimation from Images using Deep Neural Network and Sparse Ground Truth. 1987-1992 - Timothy Callemein, Kristof Van Beeck, Toon Goedemé:
Anyone here? Smart Embedded Low-Resolution Omnidirectional Video Sensor to Measure Room Occupancy. 1993-2000 - Ning Jia, Christopher J. Holder, Stephen Bonner, Boguslaw Obara:
Coarse Annotation Refinement for Segmentation of Dot-Matrix Batchcodes. 2001-2007 - Benjamin Lutz, Dominik Kißkalt, Daniel Regulin, Raven Reisch, Andreas Schiffler, Jörg Franke:
Evaluation of Deep Learning for Semantic Image Segmentation in Tool Condition Monitoring. 2008-2013 - Jing Li, Hongtao Huo, Kejian Liu, Chang Li, Shuo Li, Xin Yang:
Infrared and Visible Image Fusion via Multi-discriminators Wasserstein Generative Adversarial Network. 2014-2019 - Floris De Feyter, Dries Hulens, Bram Claes, Toon Goedemé:
Deep Diamond Re-ID. 2020-2025 - Rodrigo Leonardo, Amber Hu, Mohammad Uzair, Qiujing Lu, Iris Fu, Keishin Nishiyama, Sooraj Mangalath Subrahmannian, Divyaa Ravichandran:
Fusing Visual and Textual Information to Determine Content Safety. 2026-2031
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