The student, at the end of the course, should know the principles of computer vision and pattern recognition and the application of machine learning techniques to these topics. The student should be able to evaluate the adequacy of a computer vision system starting from requirements and considering technological constraints.
Computer Vision and Pattern Recognition
Learning Goals
Program in pills
Image formation, Image processing, Feature detection, Fitting geometric primitives, Support vector machines, Recognition, Convolutional neural networks, Camera calibration, Stereopsis, Tracking (sketches)
Area
Machine Learning and Artificial Intelligence
Curriculum Foundations
TAF Type
Curriculum Industry
TAF Type
Curriculum Health
TAF Type
Curriculum Economy
TAF Type
SSD
ECTS
Semester
Lecturers
Felice Andrea Pellegrino