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ORCID49th AIPR 2020: Washington, DC, USA
- 49th IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2020, Washington, DC, USA, October 13-15, 2020. IEEE 2020, ISBN 978-1-7281-8243-8
- Nouf Alrasheed, Arun Zachariah, Shivika Prasanna
, Deepthi S. Rao, Praveen Rao:
Deepfakes for Histopathology Images: Myth or Reality? 1-7 - Jonathan Schierl, Quinn Graehling, Theus H. Aspiras, Vijayan K. Asari, Andre van Rynbach, Dave Rabb:
Multi-modal Data Analysis and Fusion for Robust Object Detection in 2D/3D Sensing. 1-7 - Imad Eddine Toubal, Ye Duan, Deshan Yang:
Deep Learning Semantic Segmentation for High-Resolution Medical Volumes. 1-9 - Haoqi Gao, Koichi Ogawara:
Adaptive Data Generation and Bidirectional Mapping for Polyp Images. 1-6 - Alexander D. Wissner-Gross, Jared C. Willard, Noah Weston:
Tamper-Proofing Imagery from Distributed Sensors Using Learned Blockchain Consensus. 1-4 - Yasmin M. Kassim, Stefan Jaeger:
A Cell Augmentation Tool for Blood Smear Analysis. 1-6 - Emily E. Berkson, Austen Groener, Charlene Cuellar-Vite, Gary Chern, Stephen O'Neill, Michael Harner, Tyler Bartelmo, Mark D. Pritt:
Methods of Exploiting Multispectral Imagery for the Monitoring of Illicit Coca Fields. 1-11 - Murthy Jonnalagadda, Sashank Taduri, Rachana Reddy:
RealTime Traffic Management System Using Object Detection based Signal Logic. 1-5 - Gani Rahmon, Filiz Bunyak, Guna Seetharaman, Kannappan Palaniappan:
Evaluation of Different Decision Fusion Mechanisms for Robust Moving Object Detection. 1-7 - Alison Cleary, Kristopher Yoo, Paul Samuel, Sean George, Fei Sun, Steven A. Israel:
Machine Learning on Small UAVs. 1-5 - Yaa Takyiwaa Acquaah, Jonathan B. Steele, Balakrishna Gokaraju, Raymond C. Tesiero, Gregory H. Monty:
Occupancy Detection for Smart HVAC Efficiency in Building Energy: A Deep Learning Neural Network Framework using Thermal Imagery. 1-6 - Mohamed Gharibi, Praveen Rao:
RefinedFed: A Refining Algorithm for Federated Learning. 1-5 - Sanjoy Kundu, Nikhil Gunti, Bailey Hendrickson, Sunil More, Sathyanarayanan N. Aakur:
Benchmark and Evaluation of Low Resource Object Detection in Biomedical Images. 1-7 - Rumana Aktar, Virginia H. Huxley, Giovanna Guidoboni, Olga V. Glinskii, Kannappan Palaniappan:
Interactive Global Mosaic Stitching from Mesentery Video Sequences. 1-5 - Stanton R. Price, Christina H. Young, Matthew R. Maschmann, Steven R. Price:
Aiding Material Design Through Machine Learning. 1-5 - Md. Alimoor Reza, David J. Crandall:
IC-ChipNet: Deep Embedding Learning for Fine-grained Retrieval, Recognition, and Verification of Microelectronic Images. 1-10 - Samara Mayhoub, Evgeny S. Sagatov, A. A. Piluga, Andrei M. Sukhov:
Video Streaming in Ad Hoc Networks. 1-5 - Nga T. T. Nguyen, Juston S. Moore, Garrett T. Kenyon:
Using models of cortical development based on sparse coding to discriminate between real and synthetically-generated faces. 1-7 - Charlene Cuellar-Vite, Gary Chern, Austen Groener, Mark D. Pritt:
Efficient Training of Object Detection Models for Automated Target Recognition. 1-6 - Trevor M. Bajkowski, David Huangal, J. Alex Hurt, Jeffrey Dale, James M. Keller, Grant J. Scott, Stanton R. Price:
Spatiotemporal Maneuverability Hazard Analytics from Low-Altitude UAS Sensors. 1-13 - John K. Lewis, Imad Eddine Toubal, Helen Chen, Vishal Sandesera, Michael Lomnitz, Zigfried Hampel-Arias, Prasad Calyam, Kannappan Palaniappan:
Deepfake Video Detection Based on Spatial, Spectral, and Temporal Inconsistencies Using Multimodal Deep Learning. 1-9 - Shizeng Yao, Yangyang Wang, Hadi Aliakbarpour, Guna Seetharaman, Raghuveer M. Rao, Kannappan Palaniappan:
SMVNet: Deep Learning Architectures for Accurate and Robust Multi-View Stereopsis. 1-6 - Gautam Raj Mode, Khaza Anuarul Hoque:
Adversarial Examples in Deep Learning for Multivariate Time Series Regression. 1-10 - Michael Lomnitz, Zigfried Hampel-Arias, Vishal Sandesara, Simon Hu:
Multimodal Approach for DeepFake Detection. 1-9 - Addison Shaver, Zhipeng Liu, Niraj Thapa, Kaushik Roy, Balakrishna Gokaraju, Xiaohong Yuan:
Anomaly Based Intrusion Detection for IoT with Machine Learning. 1-6 - Maria Clare Lusardi, Isaac Dubovoy, Jeremy Straub:
Determining the Impact of Cybersecurity Failures During and Attributable to Pandemics and Other Emergency Situations. 1-6 - Jeffrey J. Dale, David Huangal, J. Alex Hurt, Trevor M. Bajkowski, James M. Keller, Grant J. Scott, Stanton R. Price:
Detection of unknown maneuverability hazards in low-altitude UAS color imagery using linear features. 1-9 - Steven A. Israel, John M. Irvine, Steven Tate:
Machine Learning, Compression, and Image Quality. 1-7 - Teena Sharma, Tejashwani Shah, Nishchal K. Verma, Shantaram Vasikarla:
A Review on Image Dehazing Algorithms for Vision based Applications in Outdoor Environment. 1-13 - Muhammad Habib Ur Rehman, Ahmed Mukhtar Dirir, Khaled Salah, Davor Svetinovic:
FairFed: Cross-Device Fair Federated Learning. 1-7 - K. Naveen Kumar, Chalavadi Vishnu, Reshmi Mitra, C. Krishna Mohan:
Black-box Adversarial Attacks in Autonomous Vehicle Technology. 1-7 - Zachary J. DeSantis, Matthew D. Reisman, Latisha R. Konz, Shabab E. Siddiq:
Broad Area Damage Assessment. 1-5 - Hussin K. Ragb, Ian T. Dover, Redha Ali:
Deep Convolutional Neural Network Ensemble for Improved Malaria Parasite Detection. 1-10 - Denzel Hamilton, Kevin T. Kornegay, Lanier A. Watkins:
Autonomous Navigation Assurance with Explainable AI and Security Monitoring. 1-7 - Khaled Alrawashdeh, Stephen Goldsmith:
Optimizing Deep Learning Based Intrusion Detection Systems Defense Against White-Box and Backdoor Adversarial Attacks Through a Genetic Algorithm. 1-8 - Michael J. Reale, Matthew Ochrym, Micah Church, Nicholas Goutermout, John Rubado, Maria Cornacchia:
Shape and Texture Aware Graph Processing. 1-18 - Akhil Vyas, Prasad Calyam:
An Interactive Graphical Visualization Approach to CNNs and RNNs. 1-7 - Otily Toutsop, Paige Harvey, Kevin T. Kornegay:
Monitoring and Detection Time Optimization of Man in the Middle Attacks using Machine Learning. 1-7 - Redha Ali, Russell C. Hardie, Hussin K. Ragb:
Ensemble Lung Segmentation System Using Deep Neural Networks. 1-5 - Shuyue Guan, Murray H. Loew:
Understanding the Ability of Deep Neural Networks to Count Connected Components in Images. 1-7 - Md Maruf Hossain Shuvo, Nafis Ahmed, Koundinya Nouduri, Kannappan Palaniappan:
A Hybrid Approach for Human Activity Recognition with Support Vector Machine and 1D Convolutional Neural Network. 1-5 - Noor M. Al-Shakarji, Ekincan Ufuktepe, Filiz Bunyak, Hadi Aliakbarpour, Guna Seetharaman, Kannappan Palaniappan:
Semi-automatic System for Rapid Annotation of Moving Objects in Surveillance Videos using Deep Detection and Multi-object Tracking Techniques. 1-6 - Alicia Esquivel Morel, Deniz Kavzak Ufuktepe, Robert Ignatowicz, Alexander Riddle, Chengyi Qu, Prasad Calyam, Kannappan Palaniappan:
Enhancing Network-edge Connectivity and Computation Security in Drone Video Analytics. 1-12 - Sonya J. Burroughs, Balakrishna Gokaraju, Kaushik Roy, Khoa Luu:
DeepFakes Detection in Videos using Feature Engineering Techniques in Deep Learning Convolution Neural Network Frameworks. 1-4
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