Neural Information Processing : 26th International Conference, ICONIP 2019, Sydney, NSW, Australia, December 12-15, 2019, Proceedings, Part III / edited by Tom Gedeon, Kok Wai Wong, Minho Lee.

Format:

Book

Contributor:

Gedeon, Tom., Editor.

Wong, Kok Wai, Editor.

Lee, Minho, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 11955

Theoretical Computer Science and General Issues, 2512-2029 ; 11955

Language:

English

Subjects (All):

Pattern recognition systems.

Artificial intelligence.

Computer vision.

Application software.

Computers, Special purpose.

Automated Pattern Recognition.

Artificial Intelligence.

Computer Vision.

Computer and Information Systems Applications.

Special Purpose and Application-Based Systems.

Local Subjects:

Automated Pattern Recognition.

Artificial Intelligence.

Computer Vision.

Computer and Information Systems Applications.

Special Purpose and Application-Based Systems.

Physical Description:

1 online resource (XXI, 649 pages) : 302 illustrations, 144 illustrations in color.

Edition:

1st ed. 2019.

Contained In:

Springer Nature eBook

Place of Publication:

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

System Details:

text file PDF

Summary:

The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 11955, is organized in topical sections on semantic and graph based approaches; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Contents:

Semantic and Graph Based Approaches

GL2vec: Graph Embedding Enriched by Line graphs with Edge Features

Joint Semantic Hashing using Deep Supervised and Unsupervised Methods

Label-Based Deep Semantic Hashing for Cross-Modal Retrieval

HRec: Heterogeneous Graph Embedding-Based Personalized Point-of-Interest Recommendation

Embedding and Predicting Software Security Entity Relationships: A Knowledge Graph Based Approach

SACIC: A Semantics-aware Convolutional Image Captioner using Multi-Level Pervasive Attention

One Analog Neuron Cannot Recognize Deterministic Context-Free Languages

Tag-based Semantic Features for Scene Image Classification

Integrating TM Knowledge into NMT with Double Chain Graph

Learning Transferable Policies with Improved Graph Neural Networks on Serial Robotic Structure

Visualizing Readable Instance Graphs of Ontology with Memo Graph

Spiking Neuron and Related Models

Hippocampus Segmentation in MRI Using Side U-Net Model

AutoML for DenseNet Compression

Mechanisms of Reward-Modulated STDP and Winner-Take-All in Bayesian Spiking Decision-Making Circuit

Homeostasis-based CNN-to-SNN Conversion of Inception and Residual Architectures

Training Large-Scale Spiking Neural Networks on Multi-core Neuromorphic System Using Backpropagation

Deep learning of EEG Data in the NeuCube Brain-inspired Spiking Neutral Network Architecture for a Better Understanding of Depression

Text Computing Using Neural Techniques

Watch and Ask: Video Question Generation

Multi-Perspective Denoising Reader for Multi-Paragraph Reading Comprehension

Models in the Wild: On Corruption Robustness of Neural NLP Systems

Hie-Transformer: A Hierarchical Hybrid Transformer for Abstractive Article Summarization

Target-Based Attention Model for Aspect-Level Sentiment Analysis

Keyphrase Generation with Word Attention

Dynamic Neural Language Models

A Fast Convolutional Self-attention Based Speech Dereverberation Method for Robust Speech Recognition

Option Attentive Capsule Network for Multi-choice Reading Comprehension

Exploring and Identifying Malicious Sites in Dark Web Using Machine Learning

Paragraph-Level Hierarchical Neural Machine Translation

Residual Connection-based Multi-step Reasoning via Commonsense Knowledge for Multiple Choice Machine Reading Comprehension

Zero-Shot Transfer Learning Based on Visual and Textual Resemblance

Morphological Knowledge Guided Mongolian Constituent Parsing

BERT based Hierarchical Sequence Classification for Context-aware Microblog Sentiment Analysis

Topic Aware Context Modelling for Conversation Response Generation

What a Dialogue! A Deep Neural Framework for Contextual Affect Detection

Improving student forum responsiveness: Detecting Duplicate Questions in Educational Forums

Time-series and Related Models

On Probability Calibration of Recurrent Text Recognition Network

On the Hermite Series-Based Generalized Regression Neural Networks for Stream Data Mining

Deep Hybrid Spatiotemporal networks for Continuous Pain Intensity Estimation

Sales Demand Forecast in E-commerce using a Long Short-Term Memory Neural Network Methodology

Deep Point-wise Prediction for Action Temporal Proposal

Real-time Financial Data Prediction Using Meta-cognitive Recurrent Kernel Online Sequential Extreme Learning Machine

Deep Spatial-Temporal Field for Human Head Orientation Estimation

Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People

Teacher-Student Learning and Post-Processing for Robust BiLSTM Mask-Based Acoustic Beamforming

Maxout into MDLSTM for offline Arabic handwriting recognition

Unsupervised Neural Models

Unsupervised Feature Selection Based on Matrix Factorization with Redundancy Minimization

Distance estimation for Quantum Prototypes based Clustering

Accelerating Bag-of-Words with SOM

A Deep Clustering-Guide Learning for Unsupervised Person Re-identification

Semi-Supervised Deep Learning Using Unsupervised Discriminant Projection

Unsupervised pre-training of the brain connectivity dynamic using residual D-net

Clustering Ensemble Selection with Determinantal Point Processes

Generative Histogram-based Model using Unsupervised Learning.

Other Format:

Printed edition:

ISBN:

978-3-030-36718-3

9783030367183

Access Restriction:

Restricted for use by site license.