Garzón, G., Gomez, S., Mantilla, D., & Martínez, F. (2022, July). A deep CT to MRI unpaired translation that preserve ischemic stroke lesions. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2708-2711). IEEE.

Garzon, G., Martinez, F. "Local Trajectory Occurrence Patterns for Partial Action and Gesture Recognition". International Journal on Advanced Science, Engineering and Information Technology. Vol 11. 2021.

Carrillo, F. M., Gouiffès, M., Villamizar, G. G., & Manzanera, A. (2021). A compact and recursive Riemannian motion descriptor for untrimmed activity recognition. Journal of Real-Time Image Processing, 1-14.

Local Trajectory Occurrence Patterns for Partial Action and Gesture Recognition

Gutiérrez, Y., Garzón, G., & Martínez, F. (2019, April). Towards clinical significance prediction using k trans evidences in prostate cancer. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

Garzón, G., & Martínez, F. (2019). A Fast Action Recognition Strategy Based on Motion Trajectory Occurrences. Pattern Recognition and Image Analysis, 29(3), 447-456.

Garzón, G., & Martínez, F. (2019, March). Online Action Recognition from Trajectory Occurrence Binary Patterns (ToBPs). In The International Conference on Advances in Emerging Trends and Technologies (pp. 409-418). Springer, Cham.

Moreno, W., Garzón, G., & Martínez, F. (2018, September). Frame-Level Covariance Descriptor for Action Recognition. In Colombian Conference on Computing (pp. 276-290). Springer, Cham.

Ruiz L, Guayacan L, Martínez F. (2019). Automatic polyp detection from a regional appearance model and a robust dense Hough coding. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

Moreno A., Rodríguez, J., Martínez F. (2019). Regional Multiscale Motion Representation for Cardiac Disease Prediction. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

Guayacán, L. C., Valenzuela, B., & Martinez, F. (2018, December). Parkinsonian gait characterization from regional kinematic trajectories. In 14th International Symposium on Medical Information Processing and Analysis (Vol. 10975, p. 1097502). International Society for Optics and Photonics.

Sierra, Franklin, Yesid Gutiérrez, and Fabio Martínez. "An online deep convolutional polyp lesion prediction over Narrow Band Imaging (NBI)." 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2020.

León, F., Plazas, M., & Martínez, F. (2020, January). An inception deep architecture to differentiate close-related Gleason prostate cancer scores. In 15th International Symposium on Medical Information Processing and Analysis (Vol. 11330, p. 113300D). International Society for Optics and Photonics.

Valenzuela, B., Viáfara, C., & Martínez, F. (2019, April). Analysis of worn surface images using gradient-based descriptors. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

Valenzuela, B., Salazar, I., & Martínez, F. (2019, April). Lagrangian center of mass (CoM t) magnification to stand out main parkinsonian gait events. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-5). IEEE.

Yesid Gutiérrez, John Arevalo, and Fabio Martínez "A Ktrans deep characterization to measure clinical significance regions on prostate cancer", Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 113300C (3 January 2020)

Salazar, I., Pertuz, S., Contreras, W., & Martínez, F. (2020). A convolutional oculomotor representation to model parkinsonian fixational patterns from magnified videos. Pattern Analysis and Application

Guayacán, L. C., Rangel, E., & Martínez, F. (2020, July). Towards understanding spatio-temporal parkinsonian patterns from salient regions of a 3D convolutional network. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3688-3691). IEEE.

F. Castillo, L. Bautista, Martínez F, “3d+t dense motion trajectories as kinematic primitives to recognize gestures on depth video sequences”, Revista Politécnica, vol. 15, no.29 pp.82-94, 2019. DOI: 10.33571/rpolitec.v15n29a7

Salazar, I., Pertuz, S., & Martínez, F. (2020). Multi-modal RGB-D Image Segmentation from Appearance and Geometric Depth Maps. TecnoLógicas, 23(48), 143-161.

C. Gonzalez, C.C. Viafara, J.J. Coronado, F. Martinez. (2019). Automatic recognition of worn surfaces exhibiting severe and mild abrasive wear regimes. Wear, 426, 1702-1711.

Contreras, S., Salazar, I., & Martínez, F. (2018). Parkinsonian hand tremor characterization from magnified video sequences. Proceedings Volume 10975, 14th International Symposium on Medical Information Processing and Analysis. spiedigitallibrary.

Sarmiento, E., Pico, J., & Martinez, F. (2018, April). Cardiac disease prediction from spatio-temporal motion patterns in cine-mri. In 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) (pp. 1305-1308). IEEE.

Rodríguez J., Martínez F. (2018) A Kinematic Gesture Representation Based on Shape Difference VLAD for Sign Language Recognition. In: Chmielewski L., Kozera R., Orłowski A., Wojciechowski K., Bruckstein A., Petkov N. (eds) Computer Vision and Graphics. ICCVG 2018. Lecture Notes in Computer Science, vol 11114. Springer, Cham.

Rodríguez J., Martínez F. (2018) Towards On-Line Sign Language Recognition Using Cumulative SD-VLAD Descriptors. In: Serrano C. J., Martínez-Santos J. (eds) Advances in Computing. CCC 2018. Communications in Computer and Information Science, vol 885. Springer, Cham.

Rodríguez J. et al. (2021) Understanding Motion in Sign Language: A New Structured Translation Dataset. In: Ishikawa H., Liu CL., Pajdla T., Shi J. (eds) Computer Vision – ACCV 2020. ACCV 2020. Lecture Notes in Computer Science, vol 12627. Springer, Cham.

Salazar, I., Pertuz, S., Contreras, W., & Martínez, F. (2019, October). Parkinsonian ocular fixation patterns from magnified videos and CNN features. In Iberoamerican Congress on Pattern Recognition (pp. 740-750). Springer, Cham.