Full Description
This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2024, held in Varna, Bulgaria, during September 18-20, 2024.
The 18 revised full papers presented in this book were carefully reviewed and selected from 23 submissions. They cover a wide range of topics in AI and its applications: natural language processing, sentiment analyses, image processing, optimization, reinforcement learning, from deep ANNs to spike timing NNs, applications in economics, medicine and process control.
Contents
1 Multimodal Sentiment Analysis: Recognizing Sentiment in Memes.- Remote Sensing Data for Predicting Crop Growth.- Cross-lingual Style Transfer TTS for High-quality Machine Dubbing.- An Approach to Discovering, Tracking over Time, and Summarizing Publicly Available Information on a Given Topic.- Reinforcement Learning Control of Cart Pole System with Spike Timing Neural Network Actor-critic Architecture.- Predictive and Explainable Modelling in Economics on the Case Study of Remittance Prediction Using the NeuDen AI Computational Architecture.- Deep Learning for Multi-class Diagnosis of Thyroid Disorders using Selective Features.- Medical Ultrasound Image Quality Assessment using Deep Learning.- Testing the NEAT Algorithm on a PSPACE-Complete Problem.- Investigating the Regularization of Deep Neural Networks for Affect Recognition with Relevance-Guided Local Explanations.- Layered Data-Centric AI to Streamline Data Quality Practices for Enhanced Automation.- Combining Graph NN and LLM for Improved Text-based Emotion Recognition.- A Novel Study on Modelling and Adaptive Optimal Control of a Tubular Reactor Based on Gaussian Processes.- Converging Dimensions: Information Extraction and Summarization through Multisource, Multimodal, and Multilingual Fusion.- Enhancing Question Answering in Lecture Videos with a Multimodal Retrieval Augmented Generation Framework.- Agent-based Simulation Leveraging Declarative Modeling for Efficient Resource Allocation in Emergency Scenarios.- Enhancing Security in Federated Learning: Detection of Synchronized Data Poisoning Attacks.- 3 Clinical and Acquisition Data for Optimizing MGMT Methylation Status Prediction: A Comprehensive Ensemble Strategy Emphasizing Non-Invasive Approaches.
