Εκ μέρους του καθηγ. κ. Ι. Πήτα σας ενημερώνουμε για το παρακάτω:
-Dear Autonomous Systems (cars) engineers, scientists and enthusiasts,
you are welcomed to register in the ‘Summer short course on Deep Learning and Computer Vision for Autonomous Systems 2020’ with applications on autonomous cars, drones and marine vessels.
It will take place on 17-18/8/2020 as an e-course hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform.
They will be complemented with on line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues.
As Greece had an excellent record on combatting COVID-19 (no reported case in AUTH), we shall also consider the case of a physical course at AUTH (in parallel to the e-course, same registration), if regulations permit it. See details in the course www page, as provisions slightly vary from course to course.
The short course consists of 16 1-hour lectures organized in two parts (one per day):
Part A lectures provide an in-depth presentation to autonomous systems imaging and the relevant architectures as well as a solid background on the necessary topics of computer vision (Image acquisition, camera geometry, Stereo and Multiview imaging, Mapping and Localization) and machine learning (Introduction to neural networks, Perceptron, backpropagation, Deep neural networks, Convolutional NNs).
Part B lectures provide in-depth views of the various topics encountered in autonomous systems perception, ranging from vehicle localization and mapping, to target detection and tracking, autonomous systems communications and embedded CPU/GPU computing. They also contain application-oriented lectures on autonomous drones, cars and marine vessels (e.g. for land/marine surveillance, search&rescue missions, infrastructure/building inspection and modeling, cinematography).
You can use the following link for course registration:
Early registration cutoff date is the 30th June 2020.
For questions, please contact: Ioanna Koroni <email@example.com>
The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Chair of the IEEE SPS Autonomous Systems Initiative, Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe).
AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking.
Thessaloniki is a very pleasant city at the end of August, with vibrant night-life, very close to world-class resorts in Chalkidiki peninsula. Aristotle University of Thessaloniki is the biggest University in Greece and in SE Europe. It is highly ranked internationally and its campus is at the city center.
1) Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
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) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/
5) AIIA Lab: https://aiia.csd.auth.gr/
Part A (8 hours)
1. Introduction to autonomous systems imaging
2. Introduction in computer vision
3. Image acquisition, camera geometry
4. Stereo and Multiview imaging
5. Introduction to neural networks, Perceptron, backpropagation
6. Deep neural networks. Convolutional NNs
7. Introduction to multiple drone imaging
8. Drone mission planning and control
Part B (8 hours)
1. Localization and mapping
2. Deep learning for object/target detection
3. Object tracking and 3D localization
4. Parallel GPU and multicore CPU programming. GPU programming
5. Fast convolution algorithms
6. Drone cinematography
7. Introduction to car vision
8. Introduction to autonomous marine vehicles
Prof. I. Pitas