Artificial Neural Networks and Machine Learning - ICANN 2021 : 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part III / 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, 12893

Theoretical Computer Science and General Issues, 2512-2029 ; 12893

Language:

English

Subjects (All):

Artificial intelligence.

Computer vision.

Application software.

Education-Data processing.

Pattern recognition systems.

Computer engineering.

Computer networks.

Artificial Intelligence.

Computer Vision.

Computer and Information Systems Applications.

Computers and Education.

Automated Pattern Recognition.

Computer Engineering and Networks.

Local Subjects:

Artificial Intelligence.

Computer Vision.

Computer and Information Systems Applications.

Computers and Education.

Automated Pattern Recognition.

Computer Engineering and Networks.

Physical Description:

1 online resource (XXIV, 697 pages) : 220 illustrations, 204 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 generative neural networks, graph neural networks, hierarchical and ensemble models, human pose estimation, image processing, image segmentation, knowledge distillation, and medical image processing. *The conference was held online 2021 due to the COVID-19 pandemic.

Contents:

Generative neural networks

Binding and Perspective Taking as Inference in a Generative Neural Network Model

Advances in Password Recovery using Generative Deep Learning Techniques

o 0886 - Dilated Residual Aggregation Network for Text-guided Image Manipulation

Denoising AutoEncoder based Delete and Generate Approach for Text Style Transfer

GUIS2Code: A Computer Vision Tool to Generate Code Automatically from Graphical User Interface Sketches

Generating Math Word Problems from Equations with Topic Consistency Maintaining and Commonsense Enforcement

Generative properties of Universal Bidirectional Activation-based Learning

Graph neural networks I

Joint Graph Contextualized Network for Sequential Recommendation

Relevance-Aware Q-matrix Calibration for Knowledge Tracing

LGACN: A Light Graph Adaptive Convolution Network for Collaborative Filtering

HawkEye: Cross-Platform Malware Detection with Representation Learning on Graphs

An Empirical Study of the Expressiveness of Graph Kernels and Graph Neural Networks

Multi-resolution Graph Neural Networks for PDE approximation

Link Prediction on Knowledge Graph by Rotation Embedding on the Hyperplane in the Complex Vector Space

Graph neural networks II

Contextualise Entities and Relations: An Interaction Method for Knowledge Graph Completion

Civil Unrest Event Forecasting Using Graphical and Sequential Neural Networks

Parameterized Hypercomplex Graph Neural Networks for Graph Classification

Feature Interaction Based Graph Convolutional Networks For Image-text Retrieval

Generalizing Message Passing Neural Networks to Heterophily using Position Information

Local and Non-local Context Graph Convolutional Networks for Skeleton-based Action Recognition.-STGATP: A Spatio-temporal Graph Attention Network for Long-term Traffic Prediction

Hierarchical and ensemble models

Integrating N-Gram Features into Pre-Trained Model: A Novel Ensemble Model for Multi-Target Stance Detection

Hierarchical Ensemble for Multi-view Clustering

Structure-Aware Multi-Scale Hierarchical Graph Convolutional Network for Skeleton Action Recognition

Learning Hierarchical Reasoning for Text-based Visual Question Answering

Hierarchical Deep Gaussian Processes Latent Variable Model via Expectation Propagation

Adaptive Consensus-Based Ensemble for Improved Deep Learning Inference Cost

Human pose estimation

Multi-Branch Network for Small Human Pose Estimation

PNO: Personalized Network Optimization for Human Pose and Shape Reconstruction

JointPose: Jointly Optimizing Evolutionary Data Augmentation and Prediction Neural Network for 3D Human Pose Estimation

DeepRehab: Real Time Pose Estimation on the Edge for Knee Injury Rehabilitation

Image processing

Subspace constraint for Single Image Super-Resolution

Towards Fine-Grained Control over Latent Space for Unpaired Image-to-Image Translation

FMSNet: Underwater Image Restoration by Learning from a Synthesized Dataset

Towards Measuring Bias in Image Classification

Towards Image Retrieval with Noisy Labels via Non-deterministic Features

Image segmentation

Improving Visual Question Answering by Semantic Segmentation

Weakly Supervised Semantic Segmentation with Patch-Based Metric Learning Enhancement

ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation

Depth Mapping Hybrid Deep Learning Method for Optic Disc and Cup Segmentation on Stereoscopic Ocular Fundus

RATS: Robust Automated Tracking and Segmentation of Similar Instances

Knowledge distillation

Data Diversification Revisited: Why Does It Work?

A Generalized Meta-Loss Function for Distillation Based Learning Using Privileged Information for Classification and Regression

Empirical Study of Data-Free Iterative Knowledge Distillation

Adversarial Variational Knowledge Distillation

Extract then Distill: Efficient and Effective Task-Agnostic BERT Distillation

Medical image processing

Semi-supervised Learning based Right Ventricle Segmentation Using Deep Convolutional Boltzmann Machine Shape Model

Improved U-Net for Plaque Segmentation of Intracoronary Optical Coherence Tomography Images

Approximated Masked Global Context Network for Skin Lesion Segmentation

DSNet: Dynamic Selection Network for Biomedical Image Segmentation

Computational Approach to Identifying Contrast-Driven Retinal Ganglion Cells

Radiological Identification of Hip Joint Centers from X-ray Images Using Fast Deep Stacked Network and Dynamic Registration Graph

A Two-Branch Neural Network for Non-Small-Cell Lung Cancer Classification and Segmentation

Uncertainty Quantification and Estimation in Medical Image Classification

Labeling Chest X-Ray Reports Using Deep Learning.

Other Format:

Printed edition:

ISBN:

978-3-030-86365-4

9783030863654

Access Restriction:

Restricted for use by site license.