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Tutorials about Visual Recognition and Machine Learning
The “ENS/INRIA Visual Recognition and Machine Learning Summer School 2011” has publicly available the reading materials, seminar presentations, and source code used in the event. These are characterized by a high quality, and have been elaborated by important experts in the field, such as:
This is a list of things that you can find in the online materials of the summer school [Link]:
- Materials for practical sessions:
- Image classification, Ivan Laptev, Cordelia Schmid, Josef Sivic and Andrew Zisserman.
- Category-level localization: Face detection, Ivan Laptev, Cordelia Schmid, Josef Sivic.
- Lecture slides:
- Supervised learning, SVMs, kernel methods, Francis Bach.
- Bag-of-Features models for category-level classification, Cordelia Schmid.
- Category-level localization, Andrew Zisserman.
- Learning with structured inputs and outputs, Christoph Lampert.
- Attributes for object recognition, Christoph Lampert.
- Recent progress on visual recognition, Jitendra Malik.
- The future of visual recognition, Jitendra Malik.
- Large scale learning, Léon Bottou.
- Large-scale visual recognition I, Alyosha Efros.
- Large-scale visual recognition II, Florent Perronnin.
- Human actions, Ivan Laptev.
- Using geometric information in recognition and scene analysis, Martial Hebert.
Tutorial about mosaicing
Interesting tutorial of image mosaicing that includes a presentation and related source code in Matlab. It is in Spanish.[Link]
Naive Bayes classifier
Short description of the naive Bayes classifier with an example: [Link]
Tutorials about computer vision
(Updated 22 November 2012)
