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Neural Information Processing: 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 26, 2024, Proceedings, Part XIII [Mīkstie vāki]

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  • Formāts: Paperback / softback, 451 pages, height x width: 235x155 mm, 121 Illustrations, color; 7 Illustrations, black and white; XXXIII, 451 p. 128 illus., 121 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2294
  • Izdošanas datums: 22-Aug-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819670071
  • ISBN-13: 9789819670079
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Neural Information Processing: 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 26, 2024, Proceedings, Part XIIIPalielināt
  • Formāts: Paperback / softback, 451 pages, height x width: 235x155 mm, 121 Illustrations, color; 7 Illustrations, black and white; XXXIII, 451 p. 128 illus., 121 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2294
  • Izdošanas datums: 22-Aug-2025
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819670071
  • ISBN-13: 9789819670079
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819670079.html

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.
The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Integrating Hierarchical Fine-Grained and Global Information
for Multimodal Sentiment Analysis.- Elemental Discourse Unit Guidance Based
Model for Multimodal Sentence Summarization.- DeemCLIP: Multimodal Emotion
Information Enhanced Human Action Recognition.- Can Multimodal Large Language
Model Think Analogically?.- PKRD-CoT: A unified Chain-of-thought Prompting
for Multi-Modal Large Language Models in Autonomous Driving.-
Multi-Granularity Multimodal Information Interaction for Knowledge Graph
Completion.- Graph Enhanced Cross-Modal Retrieval based on
Visual-Language Knowledge Distillation.- A Simple Interactive Attention for
Multimodal Named Entity Recognition.- Multimodal Polarity-semantic Coupling
Network for Sarcasm Analysis.- A Two-Stage Multi-Domain Collaborative
Optimization Network for 3D Human Mesh Recovery.- Supporting Event Sentence
Coreference Identification with Progressive Prompt-guided Implicit knowledge
Distillation.- CRGAT: Contextualized Relational Graph Attention Network
for Knowledge Graph Completion.- Leveled Learning: An Interpolation-Based
Data Augmentation Method on Few-Shot Text Classification.- Prompt-tuning for
Clickbait Detection via Text Summarization.- Optimizing BERT for Superior NLP
Performance: Balancing Efficiency with Advanced Pre-Training Techniques.-
EBPL: Financial Event Causality Extraction Based on Prompt Learning.- TCAN:
Triple Context-Aware Network for Multi-Modal Conversational Emotion
Recognition.- DDKG: Dual attention KG-to-text Generation with Dual-view
Graph Attention.- The Master-Slave Encoder Model for Improving Patent
Text Summarization: A New Approach to Combining Specifications and Claims.-
MulLog: A Software Defect Prediction Approach Based on Multi-Label
Contrastive Learning and Line Property Graph Learning.- Video Piracy Websites
Detection using Continual Learning with Elastic Weight Consolidation.-
MetaRAED: Meta Learning Prototype-based Retrieval Augmented Few-shot Event
Detection.- Cantonese Dialect Transcription in Diverse Sophisticated
Scenarios via the OpenAI Whisper Speech Recognition Model.- Cross-lingual
Sentence Representations via Focus Learning.- SPSEAE: Soft Prompt with
Relevant Context Aggregation for Sentence-Level Event Argument Extraction.-
HinglishCap: A Code Mixed Hindi-English Image Captioning Framework.- Silent
Intruders: Dissecting Textual Backdoor Attacks in Federated
Dialog Systems.- SBoRA: Low-Rank Adaptation with Regional Weight Updates.-
Improving Document-level Event Coreference Resolution with Knowledge
Distillation.- Improving In-Context Learning with Inquiry Style
Classification in Table Question Answering.- Role-playing based on Large
Language Models via Style Extraction.