CANUL KU, MARIO GERARDO
CIENCIAS TECNOLÓGICAS · Nivel C
Desde 2021 es Virtual Professor en Virtual University of the State of Guanajuato
Mario Canul-Ku received the B.S. degree in computer science from the University of Yucatan in 2011, and the M.Sc. and Ph.D. degrees in computer science from the Centro de Investigación en Matemáticas, Mexico, in 2013 and 2019, respectively. He is...
Mario Canul-Ku received the B.S. degree in computer science from the University of Yucatan in 2011, and the M.Sc. and Ph.D. degrees in computer science from the Centro de Investigación en Matemáticas, Mexico, in 2013 and 2019, respectively. He is currently a Postdoctoral Researcher with the Department of Computer Science, CIMAT, Mexico. His research interests include oil spill detection, machine learning, deep learning, computer vision, augmented reality, 3D shape analysis, and image SAR processing.
Información*
| Nombre | MARIO GERARDO CANUL KU |
|---|---|
| Área | INGENIERÍAS Y DESARROLLO TECNOLÓGICO |
| Campo | CIENCIAS TECNOLÓGICAS |
| Disciplina | COMPUTACIÓN |
| Especialidad | REDES |
| CVU | 421502 |
| Institución | |
|---|---|
| Dependencia | SIN INFORMACIÓN |
| Entidad | GUANAJUATO |
| Nivel | C |
| Vigencia | Inicio: 01/01/2023 |
| Fin: 31/12/2026 |
* Información del primer trimestre de 2026.
Fuente: SECIHTI.
Publicaciones ORCID
- 2024
- Super-resolution reconstruction of vertebrate microfossil computed tomography images based on deep learning X-Ray Spectrometry
- 2023
- Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation Marine Pollution Bulletin
- 2021
- Semantic segmentation of vertebrate microfossils from computed tomography data using a deep learning approach Journal of Micropalaeontology
- 2020
- ADMorph: A 3D Digital Microfossil Morphology Dataset for Deep Learning IEEE Access
- 2019
- Classification of 3D Archaeological Objects Using Multi-View Curvature Structure Signatures IEEE Access