Neural Information Processing
Springer Verlag, Singapore
978-981-99-8144-1 (ISBN)
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.
Erscheinungsdatum | 28.11.2023 |
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Reihe/Serie | Communications in Computer and Information Science |
Zusatzinfo | 174 Illustrations, color; 18 Illustrations, black and white; XXI, 597 p. 192 illus., 174 illus. in color. |
Verlagsort | Singapore |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | affective and cognitive learning • Big Data • Bioinformatics • brain-machine interface • Computational Finance • Computational Intelligence • control and decision theory • Data Mining • Human-Computer interaction • Image processing & computer vision • machine learning • Natural Language Processing • neural data analysis • neural network • Neurodynamics • Optimization • pattern recognition • Recommender Systems • Robotics and control • Social Networks |
ISBN-10 | 981-99-8144-1 / 9819981441 |
ISBN-13 | 978-981-99-8144-1 / 9789819981441 |
Zustand | Neuware |
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