IMAGE AND VIDEO UNDERSTANDING
|Academic year||2019/2020 Syllabus of previous years|
|Official course title||IMAGE AND VIDEO UNDERSTANDING|
|Course code||CM0524 (AF:306554 AR:166121)|
|Modality||On campus classes|
|Degree level||Master's Degree Programme (DM270)|
|Educational sector code||INF/01|
1.1. acquire the main models and algorithms of image and video understanding
2. Ability to apply knowledge and understanding
2.1. acquire the ability to apply the studied models to real problems
2.2. acquire the ability to critically assess the performance and the behavior of a model applied to a concrete problem
3.1. ability to understand which characteristics of the various models of artificial intelligence are best suited to a given problem
3.2. ability to critically evaluate the theoretical characteristics of the proposed models
Image and video segmentation.
Tracking and re-identification in videos.
Machine learning and (deep) neural network methods.
- D. Forsyth and J. Ponce. Computer Vision: A modern Approach. Pearson.
- I. Goodfellow, Y. Bengio and A. Courville. Deep Learning. MIT Press