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 central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through 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 approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210