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Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 2023, 2023, Proceedings, Part VI 1st ed. 2024 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 503 pages, height x width: 235x155 mm, weight: 795 g, 141 Illustrations, color; 6 Illustrations, black and white; XX, 503 p. 147 illus., 141 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14452
  • Izdošanas datums: 14-Nov-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819980755
  • ISBN-13: 9789819980758
  • Mīkstie vāki
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  • Formāts: Paperback / softback, 503 pages, height x width: 235x155 mm, weight: 795 g, 141 Illustrations, color; 6 Illustrations, black and white; XX, 503 p. 147 illus., 141 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14452
  • Izdošanas datums: 14-Nov-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819980755
  • ISBN-13: 9789819980758
The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. 

The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. 

MIC: An Effective Defense Against Word-level Textual Backdoor
Attacks.- Active Learning for Open-set Annotation Using Contrastive Query
Strategy.- Cross-Domain Bearing Fault Diagnosis Method Using Hierarchical
Pseudo Labels.- Differentiable Topics Guided New Paper Recommendation.- IIHT:
Medical Report Generation with Image-to-Indicator Hierarchical
Transformer.- OD-Enhanced Dynamic Spatial-Temporal Graph Convolutional
Network for Metro Passenger Flow Prediction.- Enhancing Heterogeneous Graph
Contrastive Learning with Strongly Correlated Subgraphs.- DRPDDet: Dynamic
Rotated Proposals Decoder for Oriented object detection.- MFSFFuse:
Multi-Receptive Field Feature Extraction for Infrared and Visible Image
Fusion using Self-Supervised Learning.- Progressive Temporal Transformer for
Bird's-Eye-View Camera Pose Estimation.- Adaptive Focal Inverse Distance
Transform Maps for Cell Recognition.- Stereo Visual Mesh for Generating
Sparse Semantic Maps at High Frame Rates.- Micro-Expression Recognition Based
on PCB-PCANet+.- Exploring Adaptive Regression Loss and Feature Focusing in
Industrial Scenarios.- Optimal Task Grouping Approach in Multitask
Learning.- Effective Guidance in Zero-Shot Multilingual Translation via
Multiple Language Prototypes.- Extending DenseHMM with Continuous
Emission.- An Efficient Enhanced-YOLOv5 Algorithm for Multi-scale Ship
Detection.- Double-Layer Blockchain-Based Decentralized Integrity
Verification for Multi-Chain Cross-Chain Data.- Inter-modal Fusion Network
with Graph Structure Preserving for Fake News Detection.- Learning to Match
Features with Geometry-aware Pooling.- PnP: Integrated Prediction and
Planning for Interactive Lane Change in Dense Traffic.- Towards Analyzing the
Efficacy of Multi-task Learning in Hate Speech Detection.- Exploring
Non-Isometric Alignment Inference for Representation Learning of Irregular
Sequences.- Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with
Sample-aware Prompting and Dynamic Revision Chain.- Improving GNSS-R Sea
Surface Wind Speed Retrieval from FY-3E Satellite Using Multi-Task Learning
and Physical Information.- Incorporating Syntactic Cognitive in
Multi-granularity Data Augmentation for Chinese Grammatical Error
Correction.- Long Short-Term Planning for Conversational Recommendation
Systems.- Gated Bi-View Graph Structure Learning.- How Legal Knowledge Graph
Can Help Predict Charges for Legal Text.- CMFN: Cross-Modal Fusion Network
for Irregular Scene Text Recognition.- Introducing Semantic-based Receptive
Field into Semantic Segmentation via Graph Neural Networks.- Transductive
Cross-Lingual Scene-Text Visual Question Answering.- Learning Representations
for Sparse Crowd Answers.- Identify Vulnerability Types: A Cross-Project
Multiclass Vulnerability Classification System based on Deep Domain
Adaptation.