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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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Chair of Computer Vision & Artificial Intelligence

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

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News

01.03.2021

We have six papers accepted to CVPR 2021!

01.03.2021

We have two papers accepted to ICRA 2021!

25.01.2021

Rick Szeliski (University of Washington) will give a talk in the TUM AI lecture series on Jan 28th, 5pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

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