Multi-disciplinary Trends in Artificial Intelligence : 17th International Conference, MIWAI 2024, Pattaya, Thailand, November 11–15, 2024, Proceedings, Part II / / edited by Chattrakul Sombattheera, Paul Weng, Jun Pang

• Autore: Sombattheera Chattrakul
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025
• Edizione: 1st ed. 2025.
• Descrizione fisica: 1 online resource (609 pages)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Artificial Intelligence
• Altri autori: WengPaul PangJun
• Nota di contenuto: -- Assessing the Influence of Epidemics on Firefighter Services: A Factor Analysis Approach. -- Fine-tuned Visualization with T-distributed Stochastic Neighbor Embeddings on Metagenomic Data for Disease Classification. -- YOLOv9c: A Robust Framework for Insect Detection. -- Assessing Factors Influencing Health Insurance Cost Prediction. -- Bagging Detection Using Transformer and Multiple Feature Fusion. -- Leveraging Pre-trained Language Models’s Performance for Emotion Recognition from Vietnamese Social Media Text. -- Leveraging OCR-Driven Information Extraction for Accurate Product Type Classification from Thai Receipt Data: An Ensemble Learning Approach. -- Speech Recognition Model for Confused Thai Lanna Vocabulary Using Deep Learning Techniques. -- Dynamic Altitude Geo Hashing based Classified billing for Haulers and Movers. -- Slide2Vid: Dynamic Video Generation from Static Presentations through Sequential Contextual Refinement. -- An Imbalance-aware Ensemble Model for Patient’s Mortality Prediction in Intensive Care Unit. -- Optimization methods for Merkle Tree in Blockchain. -- Meta-Learning in Audio and Speech Processing: An End to End Comprehensive Review. -- Fusing Object Detections to Obtain Geolocated Salient Points using Aerial Images. -- TFS recognition using MediaPipe Hands. -- Predicting Violated Law Sections using Document Classification Techniques. -- Automated Disease Detection in Millet Crops using Deep Learning. -- Automatic Knowledge Acquisition System with Large Language Model in Academic Domain. -- Graph Embeddings and DQ-Learning: Efficient Exams Scheduling. -- Implementation of a License Plate Recognition System In Vietnam Using Embedding Devices. -- A New Method of Mining High Utility Co-location Patterns from Spatial Data. -- Discovering high average utility co-location patterns using an upper bound utility and a hierarchical instance tree. -- Ensemble method for Optical Coherence Tomography Scan classification using fuzzy functions. -- Improvement of Multi-label kNN Classifier with Self-adjusting Memory Using a Punitive Model for Drifting Data Streams. -- Enhancing Post-Quantum Cryptography Security with BioCrypt Quantum Shield through Nature-Inspired Machine Learning. -- Enhancing AI Chatbots for Mental Health Support: A Comprehensive Approach. -- Ensemble Modeling for Emotion Recognition Using a Frame Attention Network on Faces With and Without Mouth Occlusion. -- Design Through AI Eyes: Automating Aesthetic Assessments for Learning. -- Design and Development of a Mobile Application for Accessible Pterygium Screening Using Pre-trained Deep Learning Models. -- An Autonomous Search System for Maritime Applications. -- Mining Quantitative Association Rules. -- Exploring Large Language Models ability to Imitate Coping’s Influence on Beliefs and Goals. -- BioMed-LLaMa-3: Instruction-Efficient Fine-Tuning of Large Language Models for Improved Biomedical Language Understanding. -- New Energy Vehicle Sales Prediction Based on Data Mining: A case study of BYD.
• Sommario/riassunto: The two-volume set LNAI 15431 and 15432 constitutes the refereed proceedings of the 17th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2024, held in Pattaya, Thailand, during November 11–15, 2024. The 68 full papers presented in these proceedings were carefully reviewed and selected from 147 submissions. The papers focus on various topics in AI and its applications, such as deep learning, machine learning, computer vision, pattern recognition, and natural language processing.
• Titolo autorizzato: Multi-disciplinary Trends in Artificial Intelligence
• ISBN: 9789819606955; 9819606950
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910983333403321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 15432