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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

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Machine Learning for Robotics and Computer Vision

WS 2013/2014, TU München

Lecture

Location: Room 02.09.023
Date: Friday, starting at 25th October
Time: 9.15
Lecturer: Dr. Rudolph Triebel
ECTS: 4
SWS: 3

Tutorial

Location: Room 02.09.023
Date: Friday, starting at 8th November
Time: 14.15
Lecturer: Matthias Vestner

The next tutorial will be on Friday, 24th January


Contents

In this lecture, the students will be introduced into the most frequently used machine learning methods in computer vision and robotics applications. The major aim of the lecture is to obtain a broad overview of existing methods, and to understand their motivations and main ideas in the context of computer vision and pattern recognition. Also, in addition to the standard methods, the lecture will also cover some recent topics such as CRFs, Random Forests, and IVMs.

Schedule:
- Introduction
- Regression
- Probabilistic Graphical Models
- Boosting
- Kernel Methods
- Gaussian Processes
- Evaluation and Model Selection
- Sampling Methods
- Clustering

Lecture Slides
Homework
Videos

Note that the video titles on YouTube start with index 1, while the lectures start with 2, so the video index is always 1 lower than the number of the lecture.

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

03.04.2022

In April 2022 Jürgen Sturm, Christian Kerl and Daniel Cremers were featured among the top 10 most influential scholars in robotics of the last decade.

31.03.2022

We have open PhD and postdoc positions! To apply, please use our application form.

08.03.2022

We have six papers accepted to CVPR 2022 in New Orleans!

31.01.2022

We have two papers accepted to ICRA 2022 - congrats to Lukas von Stumberg, Qing Cheng and Niclas Zeller!

05.12.2021
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