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ORCID29th ICANN 2020: Bratislava, Slovakia - Part I
- Igor Farkas
, Paolo Masulli, Stefan Wermter:
Artificial Neural Networks and Machine Learning - ICANN 2020 - 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15-18, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12396, Springer 2020, ISBN 978-3-030-61608-3
Adversarial Machine Learning
- Kathrin Grosse, Thomas Alexander Trost, Marius Mosbach, Michael Backes, Dietrich Klakow:
On the Security Relevance of Initial Weights in Deep Neural Networks. 3-14 - Yuchun Fang, Qicai Ran, Yifan Li:
Fractal Residual Network for Face Image Super-Resolution. 15-26 - Max Lübbering, Rajkumar Ramamurthy, Michael Gebauer, Thiago Bell, Rafet Sifa, Christian Bauckhage:
From Imbalanced Classification to Supervised Outlier Detection Problems: Adversarially Trained Auto Encoders. 27-38 - Chang Liu, Wang Lin, Zhengfeng Yang:
Generating Adversarial Texts for Recurrent Neural Networks. 39-51 - Anindya Sarkar, Raghu Sesha Iyengar:
Enforcing Linearity in DNN Succours Robustness and Adversarial Image Generation. 52-64 - Iveta Becková, Stefan Pócos, Igor Farkas:
Computational Analysis of Robustness in Neural Network Classifiers. 65-76
Bioinformatics and Biosignal Analysis
- Mikhail Tokovarov:
Convolutional Neural Networks with Reusable Full-Dimension-Long Layers for Feature Selection and Classification of Motor Imagery in EEG Signals. 79-91 - Wenwen Cui, Zhaoyang Yu, Zhuangzhuang Liu, Gang Wang, Xiaoguang Liu:
Compressing Genomic Sequences by Using Deep Learning. 92-104 - Meshal Ansari, David S. Fischer, Fabian J. Theis:
Learning Tn5 Sequence Bias from ATAC-seq on Naked Chromatin. 105-114 - Zuzana Rostáková, Roman Rosipal, Saman Seifpour:
Tucker Tensor Decomposition of Multi-session EEG Data. 115-126 - Nick Taubert, Jesse St. Amand, Prerana Kumar, Leonardo Gizzi, Martin A. Giese:
Reactive Hand Movements from Arm Kinematics and EMG Signals Based on Hierarchical Gaussian Process Dynamical Models. 127-140
Cognitive Models
- Sarah Fabi, Sebastian Otte, Jonas Gregor Wiese, Martin V. Butz:
Investigating Efficient Learning and Compositionality in Generative LSTM Networks. 143-154 - Dania Humaidan, Sebastian Otte, Martin V. Butz:
Fostering Event Compression Using Gated Surprise. 155-167 - Michael Stettler, Nick Taubert, Tahereh Azizpour, Ramona Siebert, Silvia Spadacenta, Peter W. Dicke, Peter Thier, Martin A. Giese:
Physiologically-Inspired Neural Circuits for the Recognition of Dynamic Faces. 168-179 - Michael Marino, Georg Schröter, Gunther Heidemann, Joachim Hertzberg:
Hierarchical Modeling with Neurodynamical Agglomerative Analysis. 180-191
Convolutional Neural Networks and Kernel Methods
- Argimiro Arratia, Alejandra Cabaña, José Rafael León:
Deep and Wide Neural Networks Covariance Estimation. 195-206 - Ivano Lauriola, Fabio Aiolli:
Monotone Deep Spectrum Kernels. 207-219 - Gavneet Singh Chadha, Jinwoo Kim, Andreas Schwung, Steven X. Ding:
Permutation Learning in Convolutional Neural Networks for Time-Series Analysis. 220-231
Deep Learning Applications I
- Jinghan Tan, Jun Sang, Zhili Xiang, Ying Shi, Xiaofeng Xia:
GTFNet: Ground Truth Fitting Network for Crowd Counting. 235-246 - Ilyas Sirazitdinov, Konstantin Kubrak, Semen Kiselev, Alexey Tolkachev, Maksym Kholiavchenko, Bulat Ibragimov:
Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest Radiography. 247-257 - Márton Véges, András Lorincz:
Multi-person Absolute 3D Human Pose Estimation with Weak Depth Supervision. 258-270 - Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso:
Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning. 271-283 - Sara Hahner, Rodrigo Iza-Teran, Jochen Garcke:
Analysis and Prediction of Deforming 3D Shapes Using Oriented Bounding Boxes and LSTM Autoencoders. 284-296
Deep Learning Applications II
- Kai Gao, Jian Zhang, Chen Li, Changbo Wang, Gaoqi He, Hong Qin:
Novel Sketch-Based 3D Model Retrieval via Cross-domain Feature Clustering and Matching. 299-311 - Nan Zhang, Jianzong Wang, Jian Yang, Xiaoyang Qu, Jing Xiao:
Multi-objective Cuckoo Algorithm for Mobile Devices Network Architecture Search. 312-324 - Zhuangzhuang Liu, Mingming Ren, Zhiheng Niu, Gang Wang, Xiaoguang Liu:
DeepED: A Deep Learning Framework for Estimating Evolutionary Distances. 325-336 - Oliver Gallitz, Oliver De Candido, Michael Botsch, Ron Melz, Wolfgang Utschick:
Interpretable Machine Learning Structure for an Early Prediction of Lane Changes. 337-349
Explainable Methods
- André Artelt, Barbara Hammer:
Convex Density Constraints for Computing Plausible Counterfactual Explanations. 353-365 - Izumi Karino, Yoshiyuki Ohmura, Yasuo Kuniyoshi:
Identifying Critical States by the Action-Based Variance of Expected Return. 366-378 - Fabian Hinder, Johannes Kummert, Barbara Hammer:
Explaining Concept Drift by Mean of Direction. 379-390
Few-Shot Learning
- Zhe Wang, Fanzhang Li:
Context Adaptive Metric Model for Meta-learning. 393-405 - Meng Zhou, Yaoyi Li, Hongtao Lu:
Ensemble-Based Deep Metric Learning for Few-Shot Learning. 406-418 - Hui Li, Liu Yang, Fei Gao:
More Attentional Local Descriptors for Few-Shot Learning. 419-430 - Pouya Soltani Zarrin, Christian Wenger:
Implementation of Siamese-Based Few-Shot Learning Algorithms for the Distinction of COPD and Asthma Subjects. 431-440 - Aihua Cai, Wenxin Hu, Jun Zheng:
Few-Shot Learning for Medical Image Classification. 441-452
Generative Adversarial Network
- Xiao Xu, Shiyu Feng, Zheng Wang, Lizhe Xie, Yining Hu:
Adversarial Defense via Attention-Based Randomized Smoothing. 455-466 - Alex Serban, Erik Poll, Joost Visser:
Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise. 467-478 - Laya Rafiee, Thomas Fevens:
Unsupervised Anomaly Detection with a GAN Augmented Autoencoder. 479-490 - Wen Zhou, Liming Wang, Yaohao Zheng:
An Efficient Blurring-Reconstruction Model to Defend Against Adversarial Attacks. 491-503 - Bangfeng Xia, Yueling Zhang, Weiting Chen, Xiangfeng Wang, Jiangtao Wang:
EdgeAugment: Data Augmentation by Fusing and Filling Edge Maps. 504-516 - Yuanyuan Ren, Yongjian Hu, Beibei Liu, Yixiang Xie, Yufei Wang:
Face Anti-spoofing with a Noise-Attention Network Using Color-Channel Difference Images. 517-526
Generative and Graph Models
- Hussam Almotlak, Cornelius Weber, Leyuan Qu, Stefan Wermter:
Variational Autoencoder with Global- and Medium Timescale Auxiliaries for Emotion Recognition from Speech. 529-540 - Jaehoon Koo, Diego Klabjan:
Improved Classification Based on Deep Belief Networks. 541-552 - Takaya Ueda, Yukako Tohsato, Ikuko Nishikawa:
Temporal Anomaly Detection by Deep Generative Models with Applications to Biological Data. 553-565 - Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz:
Inferring, Predicting, and Denoising Causal Wave Dynamics. 566-577 - Shuo Wang, Carsten Rudolph, Surya Nepal, Marthie Grobler, Shangyu Chen:
PART-GAN: Privacy-Preserving Time-Series Sharing. 578-593 - Changmin Wu, Giannis Nikolentzos, Michalis Vazirgiannis:
EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs. 594-606
Hybrid Neural-Symbolic Architectures
- Lei Zhong, Changmin Bai, Jianfeng Li, Tong Chen, Shigang Li:
Facial Expression Recognition Method Based on a Part-Based Temporal Convolutional Network with a Graph-Structured Representation. 609-620 - Lisa Graziani, Stefano Melacci, Marco Gori:
Generating Facial Expressions Associated with Text. 621-632 - Amit Gajbhiye, Thomas Winterbottom, Noura Al Moubayed, Steven Bradley:
Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. 633-646 - Henrique Lemos, Pedro H. C. Avelar, Marcelo O. R. Prates, Artur S. d'Avila Garcez, Luís C. Lamb:
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases. 647-659 - Alexander Sutherland, Suna Bensch, Thomas Hellström, Sven Magg, Stefan Wermter:
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE). 660-671 - Martin Takác, Alistair Knott, Mark Sagar:
SOM-Based System for Sequence Chunking and Planning. 672-684
Image Processing
- Tayssir Doghri, Leszek Szczecinski, Jacob Benesty, Amar Mitiche:
Bilinear Models for Machine Learning. 687-698 - Lecheng Zhou, Xiaodong Gu:
Enriched Feature Representation and Combination for Deep Saliency Detection. 699-710 - Huiling Wang:
Spectral Graph Reasoning Network for Hyperspectral Image Classification. 711-723 - Zhenshan Tan, Yikai Hua, Xiaodong Gu:
Salient Object Detection with Edge Recalibration. 724-735 - Junbing Li, Changqing Zhang, Xueman Wang, Ling Du:
Multi-Scale Cross-Modal Spatial Attention Fusion for Multi-label Image Recognition. 736-747 - Haocong Zheng, Yongjian Hu, Beibei Liu, Guang Chen, Alex C. Kot:
A New Efficient Finger-Vein Verification Based on Lightweight Neural Network Using Multiple Schemes. 748-758
Medical Image Processing
- Liping Yi, Jinsong Zhang, Rui Zhang, Jiaqi Shi, Gang Wang, Xiaoguang Liu:
SU-Net: An Efficient Encoder-Decoder Model of Federated Learning for Brain Tumor Segmentation. 761-773 - Yili Qu, Wanqi Su, Xuan Lv, Chufu Deng, Ying Wang, Yutong Lu, Zhiguang Chen, Nong Xiao:
Synthesis of Registered Multimodal Medical Images with Lesions. 774-786 - Tuo Leng, Yu Wang, Ying Li, Zhijie Wen:
ACE-Net: Adaptive Context Extraction Network for Medical Image Segmentation. 787-799 - Ying Li, Yu Wang, Tuo Leng, Zhijie Wen:
Wavelet U-Net for Medical Image Segmentation. 800-810
Recurrent Neural Networks
- Wei Liu, Yusen Wu, Lei Jiang, Jianfeng Fu, Weimin Li:
Character-Based LSTM-CRF with Semantic Features for Chinese Event Element Recognition. 813-824 - Moritz Wolter, Jürgen Gall, Angela Yao:
Sequence Prediction Using Spectral RNNs. 825-837 - Jatin Bedi:
Attention Based Mechanism for Load Time Series Forecasting: AN-LSTM. 838-849 - Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel:
DartsReNet: Exploring New RNN Cells in ReNet Architectures. 850-861 - Monika Schak, Alexander Gepperth:
On Multi-modal Fusion for Freehand Gesture Recognition. 862-873 - Alessandro Salatiello, Martin A. Giese:
Recurrent Neural Network Learning of Performance and Intrinsic Population Dynamics from Sparse Neural Data. 874-886
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