[visionlist] Invitation to join 2021 Summer 'Programming short course and workshop on Deep Learning and Computer Vision', 25-27th August 2021
ioannakoroni at csd.auth.gr
Thu Aug 19 00:52:24 -04 2021
Dear Machine Learning and Deep Neural Networks engineers, scientists and
you are welcomed to register in the CVML e-course on 'Programming short
course and workshop on Deep Learning and Computer Vision', 25-27th August
It will take place as a three-day e-course (due to COVID-19 circumstances),
hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki,
Greece, providing a series of live lectures and workshops delivered through
a tele-education platform (Zoom). They will be complemented with on-line
video recorded lectures and lecture pdfs, to facilitate international
participants having time difference issues and to enable you to study at own
pace. You can also self-assess your knowledge, by filling appropriate
questionnaires (one per lecture). You will be provided programming to
improve your programming skills. You will also have accesses to tutorial
exercises to better your theoretical understanding of selected CVML topics.
This course is part of the very successful CVML programming short course and
workshop series that took place in the last four years.
Course description 'Programming short course and workshop on Deep Learning
and Computer Vision'
The programming short course and workshop e-course consists of 16 1-hour
live lectures & workshops organized in two Parts (1 Part per day):
Part A will focus on Deep Learning and GPU programming.
Part B lectures will focus on deep learning algorithms for computer vision,
namely on 2D object/face detection and 2D object tracking.
Part C lectures will focus on autonomous UAV cinematography. Before mission
execution, it is best simulated, using drone mission simulation tools.
Part A (8 hours),
Deep Learning and GPU programming
Deep neural networks. Convolutional NNs.
Deep learning for target detection.
Image classification with CNNs.
Target detection with PyTorch.
Part B (8 hours), Deep Learning for Computer Vision
Deep learning for object/face detection.
2D object tracking.
PyTorch: Understand the core functionalities of an object detector. Training
OpenCV programming for object tracking.
Part C (8 hours), Autonomous UAV cinematography
Video summarization with Pytorch.
Drone cinematography with Airsim.
You can use the following link for course registration:
Lecture topics, sample lecture ppts and videos, self-assessment
questionnaires, programming exercises and tutorial exercises can be found
For questions, please contact: Ioanna Koroni <koroniioanna at csd.auth.gr
<mailto:koroniioanna at csd.auth.gr> >
The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow and
IEEE distinguished speaker. He is the coordinator of the EC funded
International AI Doctoral Academy (AIDA <http://www.i-aida.org/> ), that is
co-sponsored by all 5 European AI R&D flagship projects (H2020 ICT48). He
was initiator and first Chair of the IEEE SPS Autonomous Systems Initiative.
He is Director of the Artificial Intelligence and Information analysis Lab
(AIIA Lab), Aristotle University of Thessaloniki, Greece. He was Coordinator
of the European Horizon2020 R&D project Multidrone. He is ranked 249-top
Computer Science and Electronics scientist internationally by Guide2research
(2018). He has 33800+ citations to his work and h-index 86+.
AUTH is ranked 153/182 internationally in Computer Science/Engineering,
respectively, in USNews ranking.
1) Prof. I. Pitas:
2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/
3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/
4) International AI Doctoral Academy (AIDA): http://www.i-aida.org/
5) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/
6) AIIA Lab: https://aiia.csd.auth.gr/
Prof. I. Pitas
Director of the Artificial Intelligence and Information analysis Lab (AIIA
Aristotle University of Thessaloniki, Greece
Post scriptum: To stay current on CVML matters, you may want to register in
the CVML email list, following instructions in:
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