Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation : 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, Part I / edited by Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis.

Format:

Book

Contributor:

Tetko, Igor V., editor.

Kůrková, V. (Vera), 1948- editor.

Karpov, Pavel, editor.

Theis, Fabian, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Theoretical computer science and general issues ; SL 1, 11727.

Theoretical Computer Science and General Issues ; 11727

Language:

English

Subjects (All):

Artificial intelligence.

Optical data processing.

Computer organization.

Computers.

Algorithms.

Computer security.

Artificial Intelligence.

Image Processing and Computer Vision.

Computer Systems Organization and Communication Networks.

Information Systems and Communication Service.

Algorithm Analysis and Problem Complexity.

Systems and Data Security.

Local Subjects:

Artificial Intelligence.

Image Processing and Computer Vision.

Computer Systems Organization and Communication Networks.

Information Systems and Communication Service.

Algorithm Analysis and Problem Complexity.

Systems and Data Security.

Physical Description:

1 online resource (XXX, 839 pages) : 372 illustrations, 242 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. .

Contents:

Bidirectional associative memory with block coding: A comparison of iterative retrieval methods

Stability analysis of a generalised class of BAM neural networks with mixed delays

Dissipativity Analysis of a Class of Competitive Neural Networks with Proportional Delays

A Nonlinear Fokker-Planck Description of Continuous Neural Network Dynamics

Multi-modal associative storage and retrieval using Hopfield auto-associative memory network

Chaotic Complex-Valued Associative Memory with Adaptive Scaling Factor Independent of Multi-Values

A Comparative Analysis of Preprocessing Methods for Single-Trial Event Related Potential Detection

Sleep State Analysis using Calcium Imaging Data by Non-negative Matrix Factorization

Detection of directional information flow induced by TMS based on symbolic transfer entropy

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network

Distinguishing Violinists and Pianists based on their Brain Signals

Research on Image-to-Image Translation with Capsule Network

Multi-View Capsule Network

Advanced Capsule Networks via Context Awareness

DDRM-CapsNet: Capsule Network based on Deep Dynamic Routing Mechanism for complex data

Squeezed Very Deep Convolutional Neural Networks for Text Classification

NeuroPower: Designing Energy Efficient Convolutional Neural Network Architecture for Embedded Systems

Swap kernel regression

Model-Agnostic Explanations for Decisions using Minimal Patterns

NARPCA: Neural Accumulate-Retract PCA for Low-latency High-throughput Processing on Datastreams

An Evaluation of Various Regression Models for the Prediction of Two-Terminal Network Reliability

Capsule Generative Models

Evaluating CNNs on the Gestalt Principle of Closure

Recovering Localized Adversarial Attacks

On the Interpretation of Recurrent Neural Networks as Finite State Machines

Neural field model for measuring and reproducing time intervals

Widely Linear Complex-valued Autoencoder: Dealing with Noncircularity in Generative-Discriminative Models

NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images

Deep Semantic Asymmetric Hashing

A Neural Network for Semi-Supervised Learning on Manifolds

Counting with Analog Neurons

On the Bounds of Function Approximations

Probabilistic Bounds for Approximation by Neural Networks

Tree Memory Networks for Sequence Processing

On Deep Set Learning and the Choice of Aggregations

Hilbert Vector Convolutional Neural Network : 2D Neural Network on 1D Data

The Same Size Dilated Attention Network for Keypoint Detection

Gradient-Based Learning of Compositional Dynamics with Modular RNNs

Transfer Learning with Sparse Associative Memories

Linear Memory Networks

A Multi-Armed Bandit Algorithm Available in Stationary or Non-Stationary Environments Using Self-Organizing Maps

Cooperation and Coordination Regimes by Deep Q-Learning in Multi-agent Task Executions

Boosting Reinforcement Learning with Unsupervised Feature Extraction

A multi-objective Reinforcement Learning algorithm for JSSP

A Reinforcement Learning Approach for Sequential Spatial Transformer Networks

Deep Recurrent Policy Networks for Planning under Partial Observability

Mixed-Reality Deep Reinforcement Learning for a Reach-to-grasp Task

FMNet: Multi-Agent Cooperation by Communicating with Featured Message Network

Inferring Event-Predictive Goal-Directed Object Manipulations in REPRISE

On Unsupervised Learning of Traversal Cost and Terrain Types Identification using Self-Organizing Maps

Scaffolding Haptic Attention with Controller Gating

Benchmarking Incremental Regressors in Traversal Cost Assessment

CPG driven RBF Network Control with Reinforcement Learning for Gait Optimization of a Dung Beetle-like Robot

Training Delays in Spiking Neural Networks

An Izhikevich Model Neuron MOS Circuit for Low Voltage Operation

UAV Detection: A STDP trained Deep Convolutional Spiking Neural Network Retina-Neuromorphic Approach

Autonoumous Learning Paradigm for Spiking Neural Networks

Multi-objective Spiking Neural Network Hardware Mapping Based on Immune Genetic Algorithm

The Importance of Self-excitation in Spiking Neural Networks Evolved to Recognize Temporal Patterns

Estimating and factoring the dropout induced distribution with Gaussian mixture model

Sequence disambiguation with synaptic traces in associative neural networks

Robust Optimal-Size Implementation of Finite State Automata with Synfire Ring-Based Neural Networks

A Neural Circuit Model of Adaptive Robust Tracking Control for Continuous-Time Nonlinear Systems.

Other Format:

Printed edition:

ISBN:

978-3-030-30487-4

9783030304874

Access Restriction:

Restricted for use by site license.