23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, Tonantzintla, Mexico, October 21¿25, 2024, Proceedings, Part II Herausgegeben:Martínez-Villaseñor, Lourdes; Ochoa-Ruiz, Gilberto
23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, Tonantzintla, Mexico, October 21¿25, 2024, Proceedings, Part II Herausgegeben:Martínez-Villaseñor, Lourdes; Ochoa-Ruiz, Gilberto
The two-volume set, LNAI 15246 and 15247, constitutes the proceedings of the 23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, held in Tonantzintla, Mexico in October 21-25, 2024. The 37 full papers presented in these proceedings were carefully reviewed and selected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections: Part I - Machine Learning; Computer Vision. Part II - Intelligent Systems; Bioinformatics and Medical Applications; Natural Language Processing.
The two-volume set, LNAI 15246 and 15247, constitutes the proceedings of the 23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, held in Tonantzintla, Mexico in October 21-25, 2024.
The 37 full papers presented in these proceedings were carefully reviewed and selected from 141 submissions. The papers presented in these two volumes are organized in the following topical sections:
Part I - Machine Learning; Computer Vision.
Part II - Intelligent Systems; Bioinformatics and Medical Applications; Natural Language Processing.
.- Intelligent Systems. .- Speeding up the Multi-Objective NAS Through Incremental Learning. .- Tax Underreporting Detection using an Unsupervised Learning Approach. .- Unsupervised anomaly detection algorithms unveil relevant temporal and spatial patterns in the SARS COV2 codon usage in M´exico. .- Spatial intelligent estimation of energy consumption. .- Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem. .- Enhancing Reptile Search Algorithm Performance for the Knapsack Problem with Integration of Chaotic Map. .- Optimal Fuzzy-Genetic Self-Tuning for Tracking Photovoltaic Peak Power. .- Novel Approaches to the Minimum Identifying Code Problem Using Enhanced Genetic Algorithms. .- Bioinformatics and Medical Applications. .- Emotion recognition Method based on EEG Signal Processing, Simplified Inception Network and Discrete Model. .- Enhancing User Authentication Through EEG based P300 Speller Response. .- Detecting Alzheimer's Disease through the Use of Language Impairment Features. .- From EEG Signal Acquisition and Classification to Mobile Integration: A Comprehensive Framework. .- Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognition. .- Natural Language Processing. .- Automatic Text Summarization based on Transportation Network and Word Mover's Distances embeddings: a toy experiment. .- Identification of Fake Users in Mobile Communication Using Sentiment Analysis Techniques. .- RESTful API for intent recognition based on RASA. .- Predicting the 2024 Mexican Presidential Election with Social Media. .- Multilevel Analyses of Russian Texts with RuLingva: a case study. .- Attention + LSTM Aspect-based Sentiment Analysis for multi-label classification.
.- Intelligent Systems. .- Speeding up the Multi-Objective NAS Through Incremental Learning. .- Tax Underreporting Detection using an Unsupervised Learning Approach. .- Unsupervised anomaly detection algorithms unveil relevant temporal and spatial patterns in the SARS COV2 codon usage in M´exico. .- Spatial intelligent estimation of energy consumption. .- Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem. .- Enhancing Reptile Search Algorithm Performance for the Knapsack Problem with Integration of Chaotic Map. .- Optimal Fuzzy-Genetic Self-Tuning for Tracking Photovoltaic Peak Power. .- Novel Approaches to the Minimum Identifying Code Problem Using Enhanced Genetic Algorithms. .- Bioinformatics and Medical Applications. .- Emotion recognition Method based on EEG Signal Processing, Simplified Inception Network and Discrete Model. .- Enhancing User Authentication Through EEG based P300 Speller Response. .- Detecting Alzheimer's Disease through the Use of Language Impairment Features. .- From EEG Signal Acquisition and Classification to Mobile Integration: A Comprehensive Framework. .- Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognition. .- Natural Language Processing. .- Automatic Text Summarization based on Transportation Network and Word Mover's Distances embeddings: a toy experiment. .- Identification of Fake Users in Mobile Communication Using Sentiment Analysis Techniques. .- RESTful API for intent recognition based on RASA. .- Predicting the 2024 Mexican Presidential Election with Social Media. .- Multilevel Analyses of Russian Texts with RuLingva: a case study. .- Attention + LSTM Aspect-based Sentiment Analysis for multi-label classification.
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