Prof. Oscar Julian Perdomo Profile

Prof. Oscar Julian Perdomo

at Univ del Rosario

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Author

Publications (5)

Proceedings Article | 10 December 2021 Paper

Monitoring and evaluation of people in indoors and outdoors using deep learning

Bryan Cruz, Karen Aguía, Oscar Perdomo

Proceedings Volume 12088, 120880V (2021) https://doi.org/10.1117/12.2606334

KEYWORDS: Video, Video surveillance, Artificial intelligence, Environmental monitoring, Detection and tracking algorithms

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Proceedings Article | 10 December 2021 Paper

A deep learning model for classification of diabetic retinopathy in eye fundus images based on retinal lesion detection

Melissa delaPava, Hernan Rios, Francisco Rodríguez, Oscar Perdomo, Fabio González

Proceedings Volume 12088, 120880T (2021) https://doi.org/10.1117/12.2606319

KEYWORDS: Eye models, Image classification, Diagnostics, Convolutional neural networks, Machine learning

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Proceedings Article | 3 November 2020 Paper

Segmentation of retinal fluids and hyperreflective foci using deep learning approach in optical coherence tomography scans

Yeison D. Sanchez, Bernardo Nieto, Fabio Padilla, Oscar Perdomo, Fabio González Osorio

Proceedings Volume 11583, 115830H (2020) https://doi.org/10.1117/12.2579934

KEYWORDS: Optical coherence tomography, Image segmentation, Diagnostics

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Proceedings Article | 3 November 2020 Paper

Automatic estimation of pose and falls in videos using computer vision model

Daniela Calvache, Hernán Bernal, Juan Guarín, Karen Aguía, Alvaro David Orjuela-Cañón, Oscar J. Perdomo

Proceedings Volume 11583, 115830W (2020) https://doi.org/10.1117/12.2579615

KEYWORDS: Video, Visual process modeling, Machine vision, Computer vision technology, Computer simulations, Image processing, Computing systems, Video processing, Cameras

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Proceedings Article | 3 November 2020 Paper

Comparison of machine learning models for the prediction of cancer cells using MHC class I complexes

Mateo N., Álvaro David Orjuela Canon, Oscar Julían Perdomo Charry

Proceedings Volume 11583, 115830M (2020) https://doi.org/10.1117/12.2579602

KEYWORDS: Cancer, Machine learning, Tumor growth modeling, Oncology, Data modeling, Proteins

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