RESEARCH INTERESTS
Artificial Intelligence
Computer Vision
Machine Learning
Deep Learning
Medical Imaging
EDUCATION
Computer Science Phd candidate.
Centre de Recherche en Automatique de Nancy (CRAN) Université de Lorraine in Nancy, France.
Thesis: “Endoscopic view enhancement using deep learning-based 3d reconstruction techniques in colonoscopic applications”
Supervisors: Prof. Christian Daul, Prof. Gilberto Ochoa, Prof. Hiram Ponce
MSc with a specialty in Computer Sciences.
Universidad Panamericana Campus Aguascalientes
Thesis: "A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset"
Eng. in Artificial Intelligence.
Universidad Panamericana Campus Aguascalientes
RESEARCH PROJECTS
Enhancement processes in Medical Imaging endoscopic projects (Classification, Segmentation, and detection)
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Deep learning-based scene understanding for autonomous cars applications.
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Properties classification and prediction from molecular structures through ML approaches.
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Properties classification and prediction from molecular structures through ML approaches.
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Tiny ML approaches for sound recognition.
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STUDENTS
Efren González González
Master of Sciences
Band-gap prediction for molecular structures using Graph Convolutional Neural networks.
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Erick Gutiérrez
Master of Sciences
Artifact segmentation and detection in colonoscopic applications using Deep Learning.
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Joaquin Miranda
Master of Sciences
Deep learning-based scene understanding for autonomous cars applications.
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SOME PAPERS
A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection datasetComputers in biology and medicine 115, 103520
Click-event sound detection in automotive industry using machine/deep learning. Applied Soft Computing 108, 107465
A 3D orthogonal vision-based band-gap prediction using deep learning: A proof of concept. Computational Materials Science 202, 110967
Estimation of Low Nutrients in Tomato Crops Through the Analysis of Leaf Images Using Machine Learning. Journal of Artificial Intelligence and Technology 1 (2), 131-137