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tandil, argentina
It's currently 10:54 AM here
Joined March 21, 2015
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José Ignacio O.
@ignaciorlando
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tandil, argentina
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José Ignacio Orlando - Ingeniero de Sistemas - Estudiante de Doctorado en Matemática
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Portfolio
Portfolio
PowerPoint: University in Argentina
Learning fully-connected CRFs for blood vessel segmentation
PowerPoint: University in Argentina
Learning fully-connected CRFs for blood vessel segmentation
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Experience
Becario Doctoral
Apr 2013 - Present
Becario Doctoral en CONICET.
Mi tema de investigación es el análisis computacional de retinografías para el diagnóstico de enfermedades.
Docente
Apr 2010 - Present
Me he desempeñado como docente en numerosas cátedras de la carrera Ingeniería de Sistemas de la UNCPBA (Tandil, Argentina).
- Metodologías de desarrollo de software (2010/2011).
- Teoría de la Información (2013, actualidad).
- Taller de Imágenes Médicas (2014, actualidad).
Pasante
May 2013 - Nov 2013 (6 months, 1 day)
Trabajé como pasante durante 6 meses en el Center for Learning and Visual Computing de la École Centrale Paris, en el proyecto "Machine learning for ophthalmology", dirigido por Matthew Blaschko.
Education
Ingeniero de Sistemas
(6 years)
Qualifications
Fundamentos para la clasificación de imágenes digitales
ECImag 2012
2012
“Fundamentos para la clasificación de imágenes digitales“. Profesora: Dra. Magdalena Lucini (UNNE, Argentina), ECImag 2012: 5ta Escuela y Workshop de Ciencias
de las Imágenes, (UNL, 2012, Santa Fe, Argentina), Nota: 9 (nueve).
Image and video processing: from Mars to Hollywood with a stop at the hospital
Duke University
2013
“Image and video processing: from Mars to Hollywood with a stop at the hospital“.
Profesor: Dr. Guillermo Saphiro (Duke University, USA), Plataforma Coursera, Curso
de 9 semanas, Aprobado con distinción.
Machine Learning
Stanford University
2014
“Machine Learning“. Profesor: Dr. Andrew Ng (Stanford University, USA),
Plataforma Coursera, Curso de 10 semanas, Aprobado con distinción.
Publications
Reviewing preprocessing and feature extraction techniques for retinal blood vessel segmentation in fundus images
Mecánica Computacional Vol. 33
"Reviewing preprocessing and feature extraction techniques for retinal blood vessel segmentation in fundus images.", Orlando, J.I. & del Fresno, M., En Mecánica
Computacional, Vol. 33(42), pp 2729-2743, 2014., San Carlos de Bariloche, Argentina.
Learning fully-connected CRFs for blood vessel segmentation in retinal images
Springer
“Learning fully-connected CRFs for blood vessel segmentation in retinal images“,
Orlando J.I. and Blaschko M., Lecture Notes in Computer Sciences (LNCS), Vol 8673, pp. 634-641, 2014. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’14). ( Evaluación por pares Double-Blind y con un ratio de aceptación del 30%), Boston, USA.
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