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.
Applications.- Multi-intent Description of Keyword Expansion for Code
Search.- Few-Shot NER in Marine Ecology using Deep Learning.- Knowledge
Prompting with Contrastive Learning for Unsupervised Commonsense Question
Answering.- PTCP: Alleviate Layer Collapse in Pruning at Initialization via
Parameter Threshold Compensation and Preservation.- Hierarchical
Attribute-Based Encryption Scheme Supporting Computing Outsourcing and
Time-Limited Access in Edge Computing.- An Ontology for Industrial
Intelligent Model Library and Its Distributed Computing
Application.- Efficient Prompt Tuning for Vision and Language
Models.- Spatiotemporal PM2.5 Pollution Prediction Using Cloud-Edge
Intelligence.- From Incompleteness to Unity: A Framework for Multi-view
Clustering with Missing Values.- PLKA-MVSNet: Parallel Multi-View Stereo with
Large Kernel Convolution Attention.- Enhancement of Masked Expression
Recognition Inference Via Fusion Segmentation and Classifier.- Semantic Line
Detection Using Deep-Hough Network with Attention Mechanism and Strip
Convolution.- Adaptive Multi-hop Neighbor Selection for Few-shot Knowledge
Graph Completion.- Applications of Quantum Embedding in Computer
Vision.- Traffic Accident Forecasting Based on a GrDBN-GPR Model with
Integrated Road Features.- Phishing Scam Detection for Ethereum Based on
Community Enhanced Graph Convolutional Networks.- DTP: An Open-domain Text
Relation Extraction Method.- Exploring the Capability of ChatGPT for
Cross-Linguistic Agricultural Document Classification: Investigation and
Evaluation.-Multi-Task Feature Self-Distillation for Semi-Supervised Machine
Translation.- ADGCN: A Weakly Supervised Framework for Anomaly Detection in
Social Networks.- Light Field Image Super-Resolution via Global-View
Information Adaptation-Guided Deformable Convolution Network.- Contrastive
Learning Augmented Graph Auto-Encoder forGraph Embedding.- Enhancing Spatial
Consistency and Class-level Diversity for Segmenting Fine-grained
Objects.- Diachronic Named Entity Disambiguation for Ancient Chinese
Historical Records.- Construction and Prediction of a Dynamic
Multi-Relationship Bipartite Network.- Category-wise Fine-Tuning for Image
Multi-label Classification with Partial Labels.- DTSRN: Dynamic Temporal
Spatial Relation Network for Stock Ranking Recommendation.- Semantic
Segmentation of Multispectral Remote Sensing Images with Class Imbalance
Using Contrastive Learning.- ESTNet: Efficient Spatio-Temporal Network for
Industrial Smoke Detection.- Algorithm for Generating Tire Defect Images
Based on RS-GAN.- Novel-Registrable Weights and Region-Level Contrastive
Learning for Incremental Few-Shot Object Detection.- Hybrid U-Net: Instrument
Semantic Segmentation in RMIS.- Continual Domain Adaption for Neural Machine
Translation.- Neural-Symbolic Reasoning with External Knowledge for Machine
Reading Comprehension.- Partial Multi-label Learning via Constraint
Clustering.- Abstractive Multi-document Summarization with Cross-Documents
Discourse Relations.- MelMAE-VC: Extending Masked Autoencoders to Voice
Conversion.- Aspect-level sentiment analysis using dual probability graph
convolutional networks (DP-GCN) integrating multi-scale
information.- Privacy-preserving Image Classification and Retrieval Scheme
over Encrypted Images.- An End-To-End Structure with novel position mechanism
and improved EMD for Stock Forecasting.- Multiscale Network with Equivalent
Large Kernel Attention for Crowd Counting.- M$^3$FGM:A Node Masking and
Multi-granularity Message passing-based Federated Graph Model for
Spatial-Temporal Data Prediction.- LenANet: A Length-controllable Attention
Network for Source Code Summarization.- Self-Supervised Multimodal
Representation Learning for Product Identification and Retrieval.
Biežāk uzdotie jautājumi par e-grāmatām