Artificial Neural Networks and Machine Learning – ICANN 2020

Table of Contents

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   Book Overview
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   Chapter 1 On the Security Relevance of Initial Weights in Deep Neural Networks
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   Chapter 2 Fractal Residual Network for Face Image Super-Resolution
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   Chapter 3 From Imbalanced Classification to Supervised Outlier Detection Problems: Adversarially Trained Auto Encoders
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   Chapter 4 Generating Adversarial Texts for Recurrent Neural Networks
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   Chapter 5 Enforcing Linearity in DNN Succours Robustness and Adversarial Image Generation
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   Chapter 6 Computational Analysis of Robustness in Neural Network Classifiers
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   Chapter 7 Convolutional Neural Networks with Reusable Full-Dimension-Long Layers for Feature Selection and Classification of Motor Imagery in EEG Signals
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   Chapter 8 Compressing Genomic Sequences by Using Deep Learning
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    Chapter 9 Learning Tn5 Sequence Bias from ATAC-seq on Naked Chromatin
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    Chapter 10 Tucker Tensor Decomposition of Multi-session EEG Data
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    Chapter 11 Reactive Hand Movements from Arm Kinematics and EMG Signals Based on Hierarchical Gaussian Process Dynamical Models
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    Chapter 12 Investigating Efficient Learning and Compositionality in Generative LSTM Networks
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    Chapter 13 Fostering Event Compression Using Gated Surprise
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    Chapter 14 Physiologically-Inspired Neural Circuits for the Recognition of Dynamic Faces
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    Chapter 15 Hierarchical Modeling with Neurodynamical Agglomerative Analysis
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    Chapter 16 Deep and Wide Neural Networks Covariance Estimation
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    Chapter 17 Monotone Deep Spectrum Kernels
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    Chapter 18 Permutation Learning in Convolutional Neural Networks for Time-Series Analysis
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    Chapter 19 GTFNet: Ground Truth Fitting Network for Crowd Counting
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    Chapter 20 Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest Radiography
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    Chapter 21 Multi-person Absolute 3D Human Pose Estimation with Weak Depth Supervision
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    Chapter 22 Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning
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    Chapter 23 Analysis and Prediction of Deforming 3D Shapes Using Oriented Bounding Boxes and LSTM Autoencoders
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    Chapter 24 Novel Sketch-Based 3D Model Retrieval via Cross-domain Feature Clustering and Matching
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    Chapter 25 Multi-objective Cuckoo Algorithm for Mobile Devices Network Architecture Search
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    Chapter 26 DeepED: A Deep Learning Framework for Estimating Evolutionary Distances
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    Chapter 27 Interpretable Machine Learning Structure for an Early Prediction of Lane Changes
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    Chapter 28 Convex Density Constraints for Computing Plausible Counterfactual Explanations
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    Chapter 29 Identifying Critical States by the Action-Based Variance of Expected Return
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    Chapter 30 Explaining Concept Drift by Mean of Direction
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    Chapter 31 Context Adaptive Metric Model for Meta-learning
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    Chapter 32 Ensemble-Based Deep Metric Learning for Few-Shot Learning
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    Chapter 33 More Attentional Local Descriptors for Few-Shot Learning
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    Chapter 34 Implementation of Siamese-Based Few-Shot Learning Algorithms for the Distinction of COPD and Asthma Subjects
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    Chapter 35 Few-Shot Learning for Medical Image Classification
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    Chapter 36 Adversarial Defense via Attention-Based Randomized Smoothing
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    Chapter 37 Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise
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    Chapter 38 Unsupervised Anomaly Detection with a GAN Augmented Autoencoder
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    Chapter 39 An Efficient Blurring-Reconstruction Model to Defend Against Adversarial Attacks
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    Chapter 40 EdgeAugment: Data Augmentation by Fusing and Filling Edge Maps
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    Chapter 41 Face Anti-spoofing with a Noise-Attention Network Using Color-Channel Difference Images
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    Chapter 42 Variational Autoencoder with Global- and Medium Timescale Auxiliaries for Emotion Recognition from Speech
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    Chapter 43 Improved Classification Based on Deep Belief Networks
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    Chapter 44 Temporal Anomaly Detection by Deep Generative Models with Applications to Biological Data
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    Chapter 45 Inferring, Predicting, and Denoising Causal Wave Dynamics
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    Chapter 46 PART-GAN: Privacy-Preserving Time-Series Sharing
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    Chapter 47 EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs
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    Chapter 48 Facial Expression Recognition Method Based on a Part-Based Temporal Convolutional Network with a Graph-Structured Representation
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    Chapter 49 Generating Facial Expressions Associated with Text
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    Chapter 50 Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models
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    Chapter 51 Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases
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    Chapter 52 Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)
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    Chapter 53 SOM-Based System for Sequence Chunking and Planning
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    Chapter 54 Bilinear Models for Machine Learning
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    Chapter 55 Enriched Feature Representation and Combination for Deep Saliency Detection
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    Chapter 56 Spectral Graph Reasoning Network for Hyperspectral Image Classification
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    Chapter 57 Salient Object Detection with Edge Recalibration
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    Chapter 58 Multi-Scale Cross-Modal Spatial Attention Fusion for Multi-label Image Recognition
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    Chapter 59 A New Efficient Finger-Vein Verification Based on Lightweight Neural Network Using Multiple Schemes
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    Chapter 60 SU-Net: An Efficient Encoder-Decoder Model of Federated Learning for Brain Tumor Segmentation
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    Chapter 61 Synthesis of Registered Multimodal Medical Images with Lesions
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    Chapter 62 ACE-Net: Adaptive Context Extraction Network for Medical Image Segmentation
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    Chapter 63 Wavelet U-Net for Medical Image Segmentation
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    Chapter 64 Character-Based LSTM-CRF with Semantic Features for Chinese Event Element Recognition
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    Chapter 65 Sequence Prediction Using Spectral RNNs
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    Chapter 66 Attention Based Mechanism for Load Time Series Forecasting: AN-LSTM
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    Chapter 67 DartsReNet: Exploring New RNN Cells in ReNet Architectures
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    Chapter 68 On Multi-modal Fusion for Freehand Gesture Recognition
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    Chapter 69 Recurrent Neural Network Learning of Performance and Intrinsic Population Dynamics from Sparse Neural Data