Computer Vision: Deep Learning

Contents:
- Notions, basic techniques, and key problems in machine learning
- Defining and training deep neural network models
- Backpropagation
- Nuts and bolts in training deep neural networks
- Hyperparameter optimization
- Tensorflow
- Convolutional Neural Networks
- Object detection and image segmentation
- Visualizing and understanding deep neural networks
- Recurrent Neural Networks
- Generative Models
- U-Nets and their applications
- Model compression

Examination:
There will be independent projects in the second half of the semester (topics can be proposed by participants) that students will work on in small groups and that will serve as the basis for grading.

Lecturers

Details

Course type
Lectures
Credits
6
Term
Winter Term 2019/2020

Dates

Lecture
Takes place every week on Friday from 14:00 to 16:00 in room NB 2/99.
First appointment is on 11.10.2019
Last appointment is on 31.01.2020
Exercise
Takes place every week on Monday from 10:00 to 12:00 in room NB 3/57.
First appointment is on 14.10.2019
Last appointment is on 27.01.2020

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210