| An oculomotor digital parkinson biomarker from a deep riemannian representation J Olmos, A Manzanera, F Martínez International Conference on Pattern Recognition and Artificial Intelligence …, 2022 | 2 | 2022 |
| Riemannian SPD learning to represent and characterize fixational oculomotor Parkinsonian abnormalities J Olmos, A Manzanera, F Martínez Pattern Recognition Letters 177, 157-163, 2024 | 1 | 2024 |
| Gait patterns coded as Riemannian mean covariances to support Parkinson’s disease diagnosis J Olmos, J Galvis, F Martínez Ibero-American Conference on Artificial Intelligence, 3-14, 2022 | 1 | 2022 |
| A local volumetric covariance descriptor for markerless Parkinsonian gait pattern quantification O Mendoza, F Martínez, J Olmos Multimedia Tools and Applications 81 (21), 30733-30748, 2022 | 1 | 2022 |
| Quantification of Parkinsonian unilateral involvement from ocular fixational patterns using a deep video representation J Olmos, B Valenzuela, F Martínez Health and Technology 13 (5), 823-830, 2023 | | 2023 |
| Parkinsonian gait patterns quantification from principal geodesic analysis S Niño, JA Olmos, JC Galvis, F Martínez Pattern Analysis and Applications 26 (2), 679-689, 2023 | | 2023 |
| A Multimodal Geometric Deep Representation to Support Bi-Parametric Prostate Cancer Lesion Classification Y Gutiérrez, J Olmos, L Guayacán, F Martínez 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-4, 2023 | | 2023 |
| Exploiting Multi-Head Attention Maps Into A Deep Riemannian Representation to Quantify Pulmonary Nodules A Moreno, J Olmos, L Guayacán, F Martínez 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-4, 2023 | | 2023 |
| A Riemannian Deep Learning Representation to Describe Gait Parkinsonian Locomotor Patterns J Olmos, F Martínez 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | | 2022 |
Fabio Martínez CarrilloProfessor. Universidad Industrial de SantanderVerified email at saber.uis.edu.co
