Workload:
180 h
|
Module Number INFO-4177 |
Module Title Intelligent Systems II - Learning in Computer Vision |
Lecture Type(s) Lecture, Tutorial |
|---|---|---|
| ECTS | 6 | |
|
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
| Duration | 1 Semester | |
| Frequency | Irregular | |
| Language of instruction | English | |
| Type of Exam | Written exam (in case of a small number of participants: oral tests) |
|
| Content | Graphical Models; Bayesian Belief Networks; Markov Random Fields; Conditional Random Fields; Learning of Structured Variables; Bayesian Decision Theory; Loss-based Learning; Parameter Learning in Graphical Models; Structured Support Vector Machines; Exact and Approximate Inference Methods; Applications in Image Processing; Segmentation; Human Pose Estimation; Image Denoising; Stereo; Object Detection. |
|
| Objectives | Students learn how complicated statistical relationships can be represented with the help of graphical models. Concrete and current problems from the fields of image processing and image understanding are solved. Various learning methods make it possible to automatically set data-driven parameters and evaluate the performance achieved. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
2
3.0
ot
25
g
100
Tutorial
Ü
o
2
3.0
|
|
| Prerequisite for participation | There are no specific prerequisites. | |
| Lecturer / Other | Gehler, Lensch, MPI | |
| Literature | Vorlesungsfolien werden bereitgestellt |
|
| Last offered | Sommersemester 2020 | |
| Planned for | --- | |
| Assigned Study Areas | INFO-INFO, MEDI-APPL, MEDI-INFO, MEDI-MEDI, MEDI-VIS, ML-CS, ML-DIV | |