Advances in computational intelligence
.- Machine Learning. .- Towards Estimating Water Consumption in Semi-Arid Urban Landscaping: A Machine Learning Approach. .- Talent Identification in Football Using Supervised Machine Learning. .- Latent State Space Quantization for Learning and Exploring Goals. .- Predicting and Classifying Contami...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Cham
Springer
2025
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| Schriftenreihe: | Lecture notes in computer science
15246 |
| Schlagworte: |
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> Information technology: general issues
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| Zusammenfassung: | .- Machine Learning. .- Towards Estimating Water Consumption in Semi-Arid Urban Landscaping: A Machine Learning Approach. .- Talent Identification in Football Using Supervised Machine Learning. .- Latent State Space Quantization for Learning and Exploring Goals. .- Predicting and Classifying Contaminants in Mexican Water Bodies. .- A ConvLSTM approach for the WorldClim Dataset in Mexico. .- Building Resilience Against Climate Change, Focusing on Predicting Precipitation with Machine Learning Models on Mexico's Metropolitan Area. .- Machine Learning Approaches for Water Quality Monitoring in the Desert State of Sonora. .- Predicting Water Levels Using Gradient Boosting Regressor and LSTM Models: A Case Study of Lago de Chapala Dam. .- Efficiently Mining High Average Utility Co-location Patterns Using Maximal Cliques and Pruning Strategies. .- QUE MAX-TE-LATTE Personalized Product Recommendations in the Coffee Shop Industry: Enhancing Customer Experience and Loyalty. .- Price Estimation for Pre-Owned Vehicles Using Machine Learning. .- Algotrading R2ED: A Machine Learning Approach. .- Analysis of Predictive Factors in University Dropout Rates Using Data Science Techniques. .- Machine Learning. .- Incremental learning for object classification in a real and dynamic world. .- Easy for us, complex for AI: Assessing the coherence of generated realistic images. .- Comparative analysis of natural landmark detection in lunar terrain images. .- Exploring Anchor-Free Object Detection Models for Surgical Tool Detection: A Comparative Study of Faster-RCNN, YOLOv4, and CenterNet++. .- Smartphone-based Fuel Identification Model for Wildifire Risk Assessment using YOLOv8. 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 |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xvii, 251 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031755392 978-3-031-75539-2 |