Artificial Neural Networks and Machine Learning - ICANN 2020

Deep Learning Applications II.-Novel Sketch-based 3D Model Retrieval via Cross-domain Feature Clustering and Matching.- Multi-objective Cuckoo Algorithm for Mobile Devices Network Architecture Search.- DeepED: a Deep Learning Framework for Estimating Evolutionary Distances.- Interpretable Machine Learning Structure for an Early Prediction of Lane Changes.- Explainable Methods.- Convex Density Constraints for Computing Plausible Counterfactual Explanations.- Identifying Critical States by the Action-Based Variance of Expected Return.- Explaining Concept Drift by Means of Direction.- Few-shot Learning.- Context Adaptive Metric Model for Meta-Learning.- Ensemble-Based Deep Metric Learning for Few-Shot Learning.- More Attentional Local Descriptors for Few-shot Learning.- Implementation of Siamese-based Few-shot Learning Algorithms for the Distinction of COPD and Asthma Subjects.- Few-Shot Learning for Medical Image Classification.- Generative Adversarial Network.- Adversarial Defense via Attention-based Randomized Smoothing.- Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise.- Unsupervised Anomaly Detection with a GAN Augmented Autoencoder.- An Efficient Blurring-Reconstruction Model to Defend against Adversarial Attacks.- EdgeAugment: Data Augmentation by Fusing and Filling Edge Map.- Face Anti-spoofing with a Noise-Attention Network Using Color-Channel Difference Images.- Generative and Graph Models.- Variational Autoencoder with Global- and Medium Timescale Auxiliaries for Emotion Recognition from Speech.- Improved Classification Based on Deep Belief Networks.- Temporal Anomaly Detection by Deep Generative Models with Applications to Biological Data.- Inferring, Predicting, and Denoising Causal Wave Dynamics.- PART-GAN: Privacy-Preserving Time-Series Sharing.- EvoNet: A Neural Network for Predicting the Evolution of Dynamic Graphs.- Hybrid Neural-symbolic Architectures.- Facial Expression Recognition Method based on a Part-based TemporalConvolutional Network with a Graph-Structured Representation.- Generating Facial Expressions Associated with Text.- Image Processing.- Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models.- Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases.- Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE).- SOM-based System for Sequence Chunking and Planning.- Bilinear Models for Machine Learning.- Enriched Feature Representation and Combination for Deep Saliency Detection.- Spectral Graph Reasoning Network for Hyperspectral Image Classification.- Salient Object Detection with Edge Recalibration.- Multi-Scale Cross-Modal Spatial Attention Fusion for Multi-label Image Recognition.- A New Efficient Finger-Vein Verification Based on Lightweight Neural Network Using Multiple Schemes.- Medical Image Processing.- SU-Net: An EfficientEncoder-Decoder Model of Federated Learning for Brain Tumor Segmentation.- Synthesis of Registered Multimodal  Medical Images with Lesions.- ACE-Net: Adaptive Context Extraction Network for Medical Image Segmentation.- Wavelet U-Net for Medical Image Segmentation.- Recurrent Neural Networks.- Character-based LSTM-CRF with semantic features for Chinese Event Element Recognition.- Sequence Prediction using Spectral RNNs.- Attention Based Mechanism for Energy Load Time Series Forecasting: AN-LSTM.- DartsReNet: Exploring new RNN cells in ReNet architectures.- On Multi-modal Fusion for Freehand Gesture Recognition.- Recurrent Neural Network Learning of Performance and Intrinsic Population Dynamics from Sparse Neural Data.