Luis M. Valentín-Coronado
Orcid: 0000-0002-9874-4088
According to our database1,
Luis M. Valentín-Coronado authored at least 16 papers
between 2009 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Deep-Learning-based Electrical Fault Detection in Photovoltaic Modules through Aerial Infrared Imaging: Addressing Data Complexity.
Computación y Sistemas (CyS), 2025
Deep Learning Approaches to Bird's-Eye View Transformation and RGB-Depth Fusion in Autonomous Vehicles.
Computación y Sistemas (CyS), 2025
2024
Assessing the Impact of Data Augmentation on Photovoltaic Module Faults Detection Using Deep Learning Models.
Res. Comput. Sci., 2024
Corn/Weed Plants Detection Under Authentic Fields based on Patching Segmentation and Classification Networks.
Computación y Sistemas (CyS), 2024
Risk Assessment for Autonomous Landing in Urban Environments using Semantic Segmentation.
CoRR, 2024
Front-to-Bird's-Eye-View Transformation for Autonomous Vehicles: A Class Imbalance-Based Approach.
Proceedings of the Pattern Recognition - 16th Mexican Conference, 2024
Risk Assessment for UAV Autonomous Landing in Urban Environments Using Semantic Segmentation.
Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2024, 2024
2023
Machine-Learning Based Estimation of the Bending Magnitude Sensed by a Fiber Optic Device.
Proceedings of the Pattern Recognition - 15th Mexican Conference, 2023
Segmentation and Classification Networks for Corn/Weed Detection Under Excessive Field Variabilities.
Proceedings of the Pattern Recognition - 15th Mexican Conference, 2023
2022
Weed Classification from Natural Corn Field-Multi-Plant Images Based on Shallow and Deep Learning.
Sensors, 2022
Dust Deposition Classification on the Receiver Tube of the Parabolic Trough Collector: A Deep Learning-Based Approach.
Proceedings of the Pattern Recognition - 14th Mexican Conference, 2022
2020
Gait Activity Classification on Unbalanced Data from Inertial Sensors Using Shallow and Deep Learning.
Sensors, 2020
CoRR, 2020
2016
Reliable confirmation of an object identity by a mobile robot: A mixed appearance/localization-driven motion approach.
Int. J. Robotics Res., 2016
2014
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014
2009
Res. Comput. Sci., 2009