Tentative: linear methods for classification and regression, Gaussian processes, random forests, SVMs and kernels, convolutional neural networks, vision transformer, generative adversarial networks, diffusion models, vision-language models, structured learning, image classification, object detection, action recognition, pose estimation, face analysis, tracking, image synthesis.
The slides and recordings will be provided via sciebo.
MA-INF2201 is recommended but not required.
Wednesday, 10:15-11:45, CP1-HSZ / Hörsaal 3
Friday, 10:15-11:45, CP1-HSZ / Hörsaal 3 (every second week)
Start: Wednesday, 9.04.
Theory and programming. At least 50% of the exercise points are required to qualify for exam. The programming exercises are implemented in Python and OpenCV.
Schedule
Friday, 10:15-11:45, CP1-HSZ / Hörsaal 3 (every second week; sometimes on Wednesday)
Registration period: 01.06.-21.06.
Exam: 28.7.-29.7., 2.037, Informatikzentrum (tbc)
2nd Exam: 8.9.-9.9., 2.037, Informatikzentrum (tbc)