Advances in Computational Collective Intelligence, Kartoniert / Broschiert
Advances in Computational Collective Intelligence
- 17th International Conference, ICCCI 2025, Ho Chi Minh City, Vietnam, November 12-15, 2025, Proceedings, Part I
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Ngoc Thanh Nguyen, Vu Dinh Duc Anh, Adrianna Kozierkiewicz, Sinh Nguyen van, Manuel Nunez, Jan Treur, Gottfried Vossen
- Verlag:
- Springer, 11/2025
- Einband:
- Kartoniert / Broschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783032102010
- Artikelnummer:
- 12474503
- Umfang:
- 524 Seiten
- Gewicht:
- 785 g
- Maße:
- 235 x 155 mm
- Stärke:
- 29 mm
- Erscheinungstermin:
- 9.11.2025
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Weitere Ausgaben von Advances in Computational Collective Intelligence |
Preis |
|---|---|
| Buch, Kartoniert / Broschiert, Englisch | EUR 98,56* |
| Buch, Kartoniert / Broschiert, Englisch | EUR 164,28* |
| Buch, Kartoniert / Broschiert, Englisch | EUR 120,46* |
Klappentext
.- Collective Intelligence and Collective Decision-Making
.- Multi-Agents UAV Coordination for Evacuation Support in Disaster-Affected Areas. .- A Multi-Agent Model of Knowledge Acquisition. .- A General Framework for Collective Recommendation System using Dynamic Users Clustering. .- Which motivation strategy impacts game player the most?. .- Multidimensional vector ranking algorithm for the group recommendation system.
.- Cooperative Strategies for Decision Making and Optimization
.- Multi Objective Optimization of the Home HealthCare Optimization Problem using Machine Learning and Tabu Search. .- Parallel Memetic Differential Evolution for Minimum Sum-of-Squares Clustering. .- Performance Analysis and Optimization for a Multi-tasking Federated Learning Framework. .- Generating All Connected and Non-Isomorphic Regular Graphs Using a Constraint-Based Approach. .- Stock Price Prediction with PSO-LSTM: A Case Study on Global Corporations.
.- Computational Intelligence for Digital Content Understanding
.- Classification of Violent Scenes in Cartoon Videos Using Deep Learning Techniques. .- Real-Time Automated Detection of Violent Content in Animated Cartoons Using YOLO. .- RAViS: Region-Aware Video Style Transfer with Prompt-Based Attention. .- Chat2Edit: A Prompt-based Image Editor with Live Feedback and Parameter Recommendation. .- Integrating Local Features into Vision Transformer Architecture for Vietnamese Visual Question Answering. .- Vision Transformer explainability: Enhancing class activation map of every heads using confidence scores with perturbation. .- Enhancing Visual Question Answering with Semantic-Preserving Image Generation. .- Smart Handwritten Notes Recognition: AI-Powered Solutions for Learning Beyond.
.- Data Fusion and Application for Industry 4.0
.- Chart VQA: A Step Towards Visual Understanding. .- Mind Sparks: Detecting Aha Moments for Personalized Learning with EEG, .- BiComplex Multimodal Fusion with Entity Attention. .- Advancing Multimodal Knowledge Graph Completion with KAN Fusion and Quaternion Fourier Transform Filtering. .- Topological Framework for Exploring Imbalanced Time Series. .- Enhancing Class Incremental Learning with Fisher-Weighted Parameter Fusion and Feature Alignment. .- Predicting Thesis Orientation for Student Based on Academic Performance.
.- Natural Language Processing
.- How Good is BLI as an Alignment Measure: A Study in Word Embedding Paradigm. .- Augmenting Classical Chinese - Modern Vietnamese Couplet Parallel Corpus using LLM-assisted methods. .- Enhancing Embedding Representations for Large Language Models: A Comparative Study of the Hashing Trick and One-Hot Encoding. .- Summarizing Vietnamese Books Using a Multi-stage Hybrid Pipeline. .- Parallel speech corpus of Kazakh and Turkish languages: methodology of creation and application prospects. .- Vietnamese Question Answering on Tabular Data via Large Language Models. .- Leveraging GPT-4 for Cryptocurrency News Sentiment Detection: A Multi-Model Benchmarking. .- A Benchmark Dataset and Evaluation Framework for Vietnamese Large Language Models in Customer Support.