Module Number

ML-4511
Module Title

Machine Learning in Gaphics, Vision, and Language
Lecture Type(s)

Practical Course
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 In the summer semester
Language of instruction English
Type of Exam

Project, presentation, and written elaboration

Content

Implementation of advanced applications and programs in the intersection of machine learning in computer graphics / computer vision / natural language processing

Objectives

Students will know how to efficiently implement current machine learning approaches in the areas of segmentation, 3D reconstruction, scene analysis, rendering, interaction, or language processing. They will be able to independently plan and execute programming projects in groups using neural networks, transformers or other ML approaches for data acquisition, reconstruction and representation as well as for natural language interaction or explanation.

Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Lensch
Literature

Teilnahmevoraussetzungen: Deep Learning, von Vorteil sind Graphische Datenverarbeitung oder Computer Vision
Literatur: Entwicklungsumgebung wird zur Verfügung gestellt.

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Course prerequisites: Completion of Deep Learning; previous completion of Computer Graphics or Computer Vision is advantageous
Literature / Other information: The development environment will be made available to the students.

Last offered unknown
Planned for Sommersemester 2024
Assigned Study Areas INFO-INFO, INFO-PRAK, MEDI-APPL, MEDI-INFO, MEDI-MEDI, MEDI-PRAX, MEDI-VIS, ML-CS, ML-DIV