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ORCID23rd MICAI 2024: Tonantzintla, Mexico - Part I
- Lourdes Martínez-Villaseñor
, Gilberto Ochoa-Ruiz:
Advances in Computational Intelligence - 23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, Tonantzintla, Mexico, October 21-25, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15246, Springer 2025, ISBN 978-3-031-75539-2
Machine Learning
- Damian L. Gallegos Espinoza, Luis Garnica Chavira, Natalia Villanueva-Rosales, Juan Manuel Rodríguez Gaeta, Carmen Julia Navarro Gómez:
Towards Estimating Water Consumption in Semi-arid Urban Landscaping: A Machine Learning Approach. 3-15 - Iván Díaz de León Rodríguez, Mahdi Zareei, Alejandro De León Languré:
Talent Identification in Football Using Supervised Machine Learning. 16-27 - Artem Latyshev, Aleksandr I. Panov:
Latent State Space Quantization for Learning and Exploring Goals. 28-39 - Yusdivia Molina, Juan Vladimir Padilla López, Héctor Manuel Cárdenas Castro, Miguel González-Mendoza:
Predicting and Classifying Contaminants in Mexican Water Bodies: A Machine Learning Approach. 40-53 - Jorge Gerardo Iglesias-Ortiz, Adrián Isaí Morales-Paredes, Jesús Antonio Low-Castro Miguel González-Mendoza, Gilberto Ochoa-Ruiz:
A ConvLSTM Approach for the WorldClim Dataset in Mexico. 54-67 - Erick Hernández Silva, Israel Sánchez Miranda, Luis Ignacio Ferro Salinas, Miguel González-Mendoza:
Building Resilience Against Climate Change. Focusing on Predicting Precipitation with Machine Learning Models on Mexico's Metropolitan Area. 68-80 - Denisse Chacón Ramírez, Emilio Ríos Ochoa, Antonio Velázquez López, Neil Hernández-Gress, Miguel González-Mendoza:
Machine Learning Implementation for Water Quality Monitoring in the Desert State of Sonora. 81-100 - Jesus Dassaef López-Barrios, Ilse Karena de Anda-García, Raúl Jiménez-Cruz, Luis A. Trejo, Gilberto Ochoa-Ruiz, Miguel González-Mendoza:
Predicting Water Levels Using Gradient Boosting Regressor and LSTM Models: A Case Study of Lago de Chapala Dam. 101-120 - Vanha Tran, Thiloan Bui, Thaigiang Do, Hoangan Le:
Efficiently Mining High Average Utility Co-location Patterns Using Maximal Cliques and Pruning Strategies. 121-134 - Jorge de Jesús Luis Ortiz, Maximino Navarro, Claude Prud'Homme, Fernando Vázquez, Hiram Ponce:
QUÉ MAX-TE-LATTE Personalized Product Recommendations in the Coffee Shop Industry: Enhancing Customer Experience and Loyalty. 135-147 - Mariel Rivera, Bruno Campos, Adrián Galicia, Enrique Noguera, Hiram Ponce:
Price Estimation for Pre-owned Vehicles Using Machine Learning. 148-159 - Ruben Martinez, Diego Tinoco, Rodrigo Huerta, Emilio Flores, Hiram Ponce:
Algotrading R2ED: A Machine Learning Approach. 160-170 - Alejandro Mauricio Maqueo-Huerta, Emilio Yoltic Martínez-Gutiérrez, Rogelio Zaid Sariñana-Hernández, Favio Mariano Dileva-Charles, Neil Hernández-Gress:
Analysis of Predictive Factors in University Dropout Rates Using Data Science Techniques. 171-182
Computer Vision
- Yareli Aburto Sánchez, Eduardo F. Morales:
Incremental Learning for Object Classification in a Real and Dynamic World. 185-197 - Azuany Mila-Ceron, Zobeida Jezabel Guzman-Zavaleta, Goben Diego Constantino-Aguirre:
Easy for Us, Complex for AI: Assessing the Coherence of Generated Realistic Images. 198-209 - Cristina Pérez Ramos, Miguel Chávez Dagostino, Leopoldo Altamirano Robles:
Comparative Analysis of Natural Landmark Detection in Lunar Terrain Images. 210-221 - Carlos Aparicio, Cuauhtémoc Guerrero, Mansoor Ali Teevno, Gilberto Ochoa-Ruiz, Sharib Ali:
Exploring Anchor-Free Object Detection Models for Surgical Tool Detection: A Comparative Study of Faster-RCNN, YOLOv4, and CenterNet++. 222-235 - Jesus Antonio Low-Castro, Nima Shirzad-Ghaleroudkhani, Maziar Jamshidi, Oliver Matthias Probst-Oleszewski, Gerardo Rodriguez-Hernandez, Mustafa Gül, Gilberto Ochoa-Ruiz:
Smartphone-Based Fuel Identification Model for Wildfire Risk Assessment Using YOLOv8. 236-247
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