Artificial Neural Networks and Machine Learning ICANN 2019: Image Processing: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 1719, 2019, Proceedings, Part III 2019 ed. [Mīkstie vāki]

Unsharp Masking Layer: Injecting Prior Knowledge in Convolutional
Networks for Image Classification.- Distortion Estimation Through Explicit
Modeling of the Refractive Surface.- Eye Movement-based Analysis on
Methodologies and Efficiency in the Process of Image Noise Evaluation.-
IBDNet: Lightweight Network for On-orbit Image Blind Denoising.- Aggregating
Rich Deep Semantic Features for Fine-Grained Place Classification.- Improving
Reliability of Object Detection for Lunar Craters using Monte Carlo Dropout.-
An improved convolutional neural network for steganalysis in the scenario of
reuse of the stego-key.- A New Learning-based One Shot Detection Framework
For Natural Images.- Dense Receptive Field Network: A Backbone Network for
Object Detection.- Referring Expression Comprehension via Co-attention and
Visual Context.- Comparison between U-Net and U-ReNet models in OCR tasks.-
Severe Convective Weather Classification in Remote Sensing Images by Semantic
Segmentation.- Action Recognition Based on Divide-and-conquer.- An Adaptive
Feature Channel Weighting Scheme for Correlation Tracking.- In-silico
staining from bright-field and fluorescent images using deep learning.- A
lightweight neural network for hard exudate segmentation of fundus image.-
Attentional Residual Dense Factorized Network for Real-time Semantic
Segmentation.- Random drop loss for tiny object segmentation: Application to
lesion segmentation in fundus images.- Flow2Seg: Motion-Aided Semantic
Segmentation.- COCO_TS Dataset: Pixel-level Annotations Based on Weak
Supervision for Scene Text Segmentation.- Learning Deep Structured
Multi-Scale Features for crisp and occlusion edge detection.- Graph-Boosted
Attentive Network for Semantic Body Parsing.- A Global-Local Architecture
Constrained by Multiple Attributes for Person Re-identification.- Recurrent
Connections Aid Occluded Object Recognition by Discounting Occluders.-
Learning Relational-Structural Networks for Robust Face Alignment.- An
Efficient 3D-NAS Method for Video-based Gesture Recognition.- Robustness of
deep LSTM networks in freehand gesture recognition.- Delving into the Impact
of Saliency Detector: A GeminiNet for Accurate Saliency Detection.- FCN
Salient Object Detection Using Region Cropping.- Object-Level Salience
Detection By Progressively Enhanced Network.- Action unit assisted Facial
Expression Recognition.- Discriminative Feature Learning using Two-stage
Training Strategy for Facial Expression Recognition.- Action Units
Classification using ClusWiSARD.- Automatic Estimation of Dog Age: The DogAge
Dataset and Challenge.- Neural Network 3D Body Pose Tracking and Prediction
for Motion-to-Photon Latency  Compensation in Distributed Virtual Reality.-
Variational Deep Embedding with Regularized Student-t Mixture Model.- A
mixture-of-experts model for vehicle prediction using an online learning
approach.- An Application of Convolutional Neural Networks for Analyzing
Dogs' Sleep Patterns.- On the Inability of Markov Models to Capture
Criticality in Human Mobility.- LSTM with Uniqueness Attention for Human
Activity Recognition.- Comparative Research on SOM with Torus and Sphere
Topologies for Peculiarity Classification of Flat Finishing Skill Training.-
Generative Creativity: Adversarial Learning for Bionic Design.-
Self-attention StarGAN for Multi-domain Image-to-image Translation.-
Generative Adversarial Networks for Operational Scenario Planing of Renewable
Energy Farms: A Study on Wind and Photovoltaic.- Constraint-Based Visual
Generation.- Text to Image Synthesis based on Multiple Discrimination.-
Disentangling Latent Factors of Variational Auto-Encoder with Whitening.-
Training Discriminative Models to Evaluate Generative Ones.- Scene Graph
Generation via Convolutional Message Passing and Class-aware Memory
Embeddings.- Change Detection in Satellite Images using Reconstruction Errors
of Joint Autoencoders.- Physical Adversarial Attacks by Projecting
Perturbations.- Improved Forward-backward Propagation to Generate Adversarial
Examples.- Incremental Learning of GAN for Detecting Multiple Adversarial
Attacks.- Evaluating Defensive Distillation For Defending Text Processing
Neural Networks Against Adversarial Examples.- DCT:Differential Combination
Testing of Deep Learning Systems.- Restoration as a Defense Against
Adversarial Perturbations for Spam Image Detection.- HLR: Generating
Adversarial Examples by High-Level Representations.