Goal: Improve your programming knowledge on Computer Vision, Machine Learning and Image/Video Processing topics using OpenCV, PyTorch and CUDA and your skills on building, e.g.. Convolutional Neural Networks and applying object tracking methods.
- CUDA programming of 2D convolution algorithms
- Digital Image Filtering Using OpenCV
- Histogram and Convolution
- Histogram Equalization
Neural Networks/Deep Learning
Signals and Systems
Help files for each exercise are available by the exercise tutor M. Kaseris, by sending message to firstname.lastname@example.org.
Such programming exercises are typically given to the Summer CVML school organized by AIIA lab each year (see http://icarus.csd.auth.gr/aiia-summer-school-on-autonomous-systems-2020/).
The solutions to the exercises will be automatically available to the registrants of the live CVML course http://icarus.csd.auth.gr/cvml-for-autonomous-systems/
and the asynchronous course 2020 CVML Web Lecture Series – Fall Edition.
For any requests, please contact the coordinator of the CVML Programming Exercises, Prof. Ioannis Pitas at: email@example.com.
Context: The above exercises have been developed by AIIA students and researchers in the framework of EC-funded R&D projects MULTIDRONE or AerialCore or for AUTH undergraduate and graduate courses on Computer Vision, Pattern Recognition, Machine Learning and Image/Video processing.
Upload your own exercise: Competent students and researchers worldwide may be interested to upload their own CVML programming exercises, after successful peer review. The above structure and rules will apply.
Your name will appear as exercise author. The aim is to build a comprehensive CVML programming exercise toolkit. If you are interested in this option, contact Prof. Ioannis Pitas at: firstname.lastname@example.org.