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Introducción a la Vision Computacional

En este repositorio hay notebooks de Jupyter para la clase de Introducción a la Visión Computacional para estudiantes de Magister y Diplomado en Data Science de la Universidad del Desarrollo.

El material proviene principalmente del libro Programming Computer Vision with Python de Jan Erik Solem, de los sitios de los cursos Computer Vision: Foundations and Applications (CS131) y Convolutional Neural Networks for Visual Recognition (CS231) de la Universidad de Stanford y del sitio Pyimagesearch de Adrian Rosebrock.

Programa

Clase Fecha Contenido Slides Notebook
1 30-08-2019 Introducción a cv, estado del arte, principales librerías para manipulacion básica de imágenes clase_01.pdf notebook_01.ipynb
2 26-10-2019 Detección de caracteristicas, esquinas y bordes, algoritmos: harris corner detector y sift clase_02.pdf notebook_2.ipynb
3 15-11-2019 Translaciónes, rotaciones y homografías. Alineación de imágenes y construcción de panorámicas clase_03.pdf notebook_3.ipynb
4 16-11-2019 Segmentación y clusterización de imágenes clase_04.pdf notebook_4.ipynb
5 16-11-2019 Extracción de caracteristicas con redes neuronales, algoritmos: tsne y umap, reconocimiento facial clase_05.pdf notebook_5.ipynb

Bibliografía

intro_computer_vision's People

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