Artificial Neural Networks and Machine Learning - ICANN 2021 : 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part II / edited by Igor Farkaš, Paolo Masulli, Sebastian Otte, Stefan Wermter.

Format:

Book

Contributor:

Farkaš, Igor., Editor.

Masulli, Paolo, Editor.

Otte, Sebastian., Editor.

Wermter, Stefan, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 12892

Theoretical Computer Science and General Issues, 2512-2029 ; 12892

Language:

English

Subjects (All):

Artificial intelligence.

Computer engineering.

Computer networks.

Application software.

Computer vision.

Artificial Intelligence.

Computer Engineering and Networks.

Computer and Information Systems Applications.

Computer Vision.

Local Subjects:

Artificial Intelligence.

Computer Engineering and Networks.

Computer and Information Systems Applications.

Computer Vision.

Physical Description:

1 online resource (XXIII, 651 pages) : 229 illustrations, 219 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as computer vision and object detection, convolutional neural networks and kernel methods, deep learning and optimization, distributed and continual learning, explainable methods, few-shot learning and generative adversarial networks. *The conference was held online 2021 due to the COVID-19 pandemic.

Contents:

Computer vision and object detection

Selective Multi-Scale Learning for Object Detection

DRENet: Giving Full Scope to Detection and Regression-based Estimation for Video Crowd Counting

Sisfrutos Papaya: a Dataset for Detection and Classification of Diseases in Papaya

Faster-LTN: a neuro-symbolic, end-to-end object detection architecture

GC-MRNet: Gated Cascade Multi-stage Regression Network for Crowd Counting

Latent Feature-Aware and Local Structure-Preserving Network for 3D Completion from a single depth view

Facial Expression Recognition by Expression-Specific Representation Swapping

Iterative Error Removal for Time-of-Flight Depth Imaging

Blurred Image Recognition: A Joint Motion Deblurring and Classification Loss-Aware Approach

Learning How to Zoom in: Weakly Supervised ROI-based-DAM for Fine-Grained Visual Classification

Convolutional neural networks and kernel methods

(Input) Size Matters for CNN Classifiers

Accelerating Depthwise Separable Convolutions with Vector Processor

KCNet: Kernel-based Canonicalization Network for entities in Recruitment Domain

Deep Unitary Convolutional Neural Networks

Deep learning and optimization I

DPWTE: A Deep Learning Approach to Survival Analysis using a Parsimonious Mixture of Weibull Distributions

First-order and second-order variants of the gradient descent in a unified framework

Bayesian optimization for backpropagation in Monte-Carlo tree search

Growing Neural Networks Achieve Flatter Minima

Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks

Curved SDE-Net Leads to Better Generalization for Uncertainty Estimates of DNNs

EIS - Efficient and Trainable Activation Functions for Better Accuracy and Performance

Deep learning and optimization II

Why Mixup Improves the Model Performance

Mixup gamblers: Learning to abstain with auto-calibrated reward for mixed samples

Non-Iterative Phase Retrieval With Cascaded Neural Networks

Incorporating Discrete Wavelet Transformation Decomposition Convolution into Deep Network to Achieve Light Training

MMF: A loss extension for feature learning in open set recognition

On the selection of loss functions under known weak label models

Distributed and continual learning

Bilevel Online Deep Learning in Non-stationary Environment

A Blockchain Based Decentralized Gradient Aggregation Design for Federated Learning

Continual Learning for Fake News Detection from Social Media

Balanced Softmax Cross-Entropy for Incremental Learning

Generalised Controller Design using Continual Learning

DRILL: Dynamic Representations for Imbalanced Lifelong Learning

Principal Gradient Direction and Confidence Reservoir Sampling for Continual Learning

Explainable methods

Spontaneous Symmetry Breaking in Data Visualization

Deep NLP Explainer: Using Prediction Slope To Explain NLP Models

Empirically explaining SGD from a line search perspective

Towards Ontologically Explainable Classifiers

Few-shot learning

Leveraging the Feature Distribution in Transfer-based Few-Shot Learning

One-Shot Meta-Learning for Radar-Based Gesture Sequences Recognition

Few-Shot Learning With Random Erasing and Task-Relevant Feature Transforming

Fostering Compositionality in Latent, Generative Encodings to Solve the Omniglot Challenge

Better Few-shot Text Classification with Pre-trained Language Model

Generative adversarial networks

Leveraging GANs via Non-local Features

On Mode Collapse in Generative Adversarial Networks

Image Inpainting Using Wasserstein Generative Adversarial Imputation Network

COViT-GAN: Vision Transformer for COVID-19 Detection in CT Scan Images with Self-Attention GAN for Data Augmentation

PhonicsGAN: Synthesizing Graphical Videos from Phonics Songs

A Progressive Image Inpainting Algorithm with a Mask Auto-update Branch

Hybrid Generative Models for Two-Dimensional Datasets

Towards Compressing Efficient Generative Adversarial Networks for Image Translation via Pruning and Distilling

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Other Format:

Printed edition:

ISBN:

978-3-030-86340-1

9783030863401

Access Restriction:

Restricted for use by site license.