Neural Information Processing
Springer Verlag, Singapore
978-981-99-8147-2 (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.- 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.
| Erscheinungsdatum | 28.11.2023 |
|---|---|
| Reihe/Serie | Communications in Computer and Information Science |
| Zusatzinfo | 169 Illustrations, color; 33 Illustrations, black and white; XXI, 613 p. 202 illus., 169 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 | 981-99-8147-6 / 9819981476 |
| ISBN-13 | 978-981-99-8147-2 / 9789819981472 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
