Artificial Intelligence – COMIA 2025 : 17th Mexican Congress, Mexico City, Mexico, May 12–16, 2025, Proceedings, Part II

著者名：Martínez-Villaseñor, Lourdes (EDT)/Martínez-Seis, Bella (EDT)/Pichardo, Obdulia (EDT)

Springer（2025/09/26発売）

• 言語：ENG
• ISBN：9783031979095
• eISBN：9783031979101

Description

The 3-volume set CCIS 2552 - 2554 constitutes the proceedings of the 17th Mexican Conference on Artificial Intelligence, COMIA 2025, which took place in Mexico City, Mexico, during May 12-16, 2025.

The totel of 83 papers included in the proceedings was carefully reviewed and selected from 199 submissions. They were organized in topical sections as follows:

Part I: Natural languages processing; robotics; signal processing; ethics and regulation;

Part II: Computer Vision and Image Processing; Deep Learning; Machine Learning and Pattern Recognition; Data Mining;

Part III: Artificial intelligence applications; medical applications.

Table of Contents

.- Computer Vision and Image Processing

.- Identification of Dangerous Driving Patterns through Computer Vision and Deep Learning.
.- Fire risk assessment in San Luis Potos´ı’s middle zone through CBIR and evolutionary computation techniques for land image analysis.
.- Embedded system for weapon and intimidation position recognition with alerts sent to smartphones.
.- Eye Feature Segmentation for the Identification of Artificially Generated Faces.
.- Encoder-decoder neural network model inspired by retinal signal processing in the retina and decoding in the visual cortex.
.- Automated design of interest point detectors using grammatical evolution.
.- Fruit Fly Classification (Diptera: Tephritidae) in Images, Applying Transfer Learning.
.- Stress Detection of Students via Low-Resolution Thermal Images using ROIs.
.- ARCanvas: A Mobile-based Collaborative Colocated AR Drawing Application.
.- Identification of Wildfire Risk Areas Through Semantic Segmentation.
.- Detection of Physical Violence at Schools Using Machine Learning and Computer Vision.
.- Alternative Strategies for Feature Engineering in a Mexican Sign Language Recognition.
.- Digital Image Synthesis Using Multi-Tree Genetic Programming.
.- Representation of Neuro-Symbolic Networks for sub-algebraic terms.

.- Deep Learning

.- Enhancing Intrusion Detection via Hierarchical Transfer Learning for Real Network Traffic.
.- Filtering of Geophysical Data Using Unsupervised Methods and Multiresolution Analysis.

.- Machine Learning and Pattern Recognition

.- A study for air quality analysis in the city of Puebla.
.- Predicting Complete Pass Probabilities with Graphs.
.- Optimized Photovoltaic Energy Forecasting through Extended Data and Python-Based Artificial Neural Networks.
.- Improved MDLP Algorithm for Supervised Discretization of Continuous Data.
.- Human-friendly Explanations Checklist for Reinforcement Learning: XRL H-F-E Checklist.
.- Reinforcement Learning in Urbanism: Building the Cities of the Future with AI.

.- Data Mining

.- Predicting Hardness and Elastic Modulus of Cast Aluminum Alloys from Chemical Composition Using Artificial Neural Networks.
.- Gini Index-Based Identification of Predictors for Undergraduate Academic Performance.
.- Optimizing Food Traceability through QR, NFC, IoT Technologies, and Artificial Intelligence to Enhance Food Safety and Reduce Waste.
.- Characterization and classification of Mexican woods by local texture analysis using deep learning techniques.
.- Estimating Evapotranspiration Using Random Forest Regression and Remote Sensing Data.