Neural Information Processing : 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part XII / edited by Biao Luo, Long Cheng, Zheng-Guang Wu, Hongyi Li, Chaojie Li.

Format:

Book

Contributor:

Luo, Biao, editor.

Series:

Communications in Computer and Information Science, 1865-0937 ; 1966

Language:

English

Subjects (All):

Pattern recognition systems.

Computer science.

Data mining.

Data structures (Computer science).

Information theory.

Automated Pattern Recognition.

Theory and Algorithms for Application Domains.

Data Mining and Knowledge Discovery.

Data Structures and Information Theory.

Local Subjects:

Automated Pattern Recognition.

Theory and Algorithms for Application Domains.

Data Mining and Knowledge Discovery.

Data Structures and Information Theory.

Physical Description:

1 online resource (632 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

Contents:

Applications

PBTR: Pre-training and Bidirectional Semantic Enhanced Trajectory Recovery

Event-aware Document-level Event Extraction via Multi-granularity Event Encoder

Curve Enhancement: A No-Reference Method for Low-light Image Enhancement

A deep joint model of Multi-Scale intent-slots Interaction with Second-Order Gate for SLU

Instance-aware and Semantic-guided Prompt for Few-shot Learning in Large Language Models

Graph Attention Network Knowledge Graph Completion Model Based on Relational Aggregation

SODet: A LiDAR-based Object Detector in Bird’s-Eye View

Landmark-assisted Facial Action Unit Detection with Optimal Attention and Contrastive Learning

Multi-Scale Local Region-Based Facial Action Unit Detection with Graph Convolutional Network

CRE: An Efficient Ciphertext Retrieval Scheme based on Encoder

Sentiment Analysis Based on Pre-trained Language Models: Recent Progress

Improving Out-of-Distribution Detection with Margin-Based Prototype Learning

Text-to-Image Synthesis With Threshold-Equipped Matching-Aware GAN

Joint Regularization Knowledge Distillation

Dual-Branch Contrastive Learning for Network Representation Learning

Multi-Granularity Contrastive Siamese Networks for Abstractive Text Summarization

Joint Entity and Relation Extraction for Legal Documents based on Table Filling

Dynamic Knowledge Distillation for Reduced Easy Examples

Fooling Downstream Classifiers via Attacking Contrastive Learning Pre-trained Models

Feature Reconstruction Distillation with Self-attention

DAGAN: Generative Adversarial Network with Dual Attentionenhanced GRU for Multivariate Time Series Imputation

Knowledge-Distillation-Warm-Start Training Strategy for Lightweight Super-Resolution Networks

SDBC: A Novel and Effective Self-Distillation Backdoor Cleansing Approach

An Alignment and Matching Network with Hierarchical Visual Features for Multimodal Named Entity and Relation Extraction

Multi-view Consistency View Synthesis

A reinforcement learning-based controller designed for Intersection signal suffering from Information Attack

Dual-Enhancement Model of Entity Pronouns and Evidence Sentence for Document-level Relation Extraction

Nearest Memory Augmented Feature Reconstruction for Unified Anomaly Detection

Deep Learning Based Personalized Stock Recommender System

Feature-Fusion-Based Haze Recognition in Endoscopic Images

Retinex Meets Transformer: Bridging Illumination and Reflectance Maps for Low-light Image Enhancement

Make Spoken Document Readable: Leveraging Graph Attention Networks for Chinese Document-Level Spoken-to-Written Simplification

MemFlowNet: A Network for Detecting Subtle Surface Anomalies with Memory Bank and Normalizing Flow

LUT-LIC: Look-up Table-Assisted Learned Image Compression

Oil and GasAutomatic Infrastructure Mapping: Leveraging HighResolution Satellite Imagery through fine-tuning of object detection models

AttnOD: An Attention-based OD Prediction Model with Adaptive Graph Convolution

CMMix: Cross-Modal Mix Augmentation between Images and Texts for Visual Grounding

A Relation-oriented Approach for Complex Entity Relation Extraction

A Revamped Sparse Index Tracker leveraging $K$–\,Sparsity and Reduced Portfolio Reshuffling

Anomaly detection of fixed-wing unmanned aerial vehicle (UAV) based on cross-feature-attention LSTM network

Spatial and Frequency Domains Inconsistency Learning for Face Forgery Detection

Enhancing Camera Position Estimation by Multi-View Pure Rotation Recognition and Automated Annotation Learning

Detecting Adversarial Examples Via Classification Difference of a Robust Surrogate Model

Minimizing Distortion in Linguistic Steganography via Adaptive Language Model Tuning

Efficient Chinese Relation Extraction with Multi-entity Dependency Tree Pruning and Path-Fusion

A lightweight text classification model based on Label Embedding Attentive mechanism.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Luo, Biao Neural Information Processing

ISBN:

981-9981-48-4