Invitation to Summer short e-course on Deep Learning and Computer Vision for Autonomous Systems 2020, 17-18th August 2020

Εκ μέρους του καθηγ. κ. Ι. Πήτα σας ενημερώνουμε για το παρακάτω:

Dear Autonomous Systems engineers, scientists and enthusiasts,

you are welcomed to register in the ‘Summer short e-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 (due to COVID-19 circumstances), 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 and to enable everybody to study at own pace.

The short e-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 CVML computing environments. 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).

You can use the following link for course registration:

Lecture topics, sample lecture ppts and videos can be found therein.

For questions, please contact: Ioanna Koroni <>

You may also want to register to the complementing ‘Programming course on Autonomous Systems’ 19-21/08/2020:

providing skills for programming autonomous systems,  focusing on drones (Pytorch, Tensorflow, OpenCV, CUDA, ROS, Gazebo, AirSim).

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.

Relevant links:

1) Prof. I. Pitas:

2) Horizon2020 EU funded R&D project Aerial-Core:

3) Horizon2020 EU funded R&D project Multidrone:

4) Horizon2020 EU funded R&D project AI4Media:

5) AIIA Lab:

Course description

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,
  6. Multilayer perceptron. Backpropagation
  7. Deep neural networks. Convolutional NNs
  8. Introduction to multiple drone imaging

Part B (8 hours)

  1. Localization and mapping
  2. Deep learning for object/target detection
  3. Object tracking and 3D localization
  4. CVML software development tools
  5. Fast convolution algorithms
  6. Drone mission planning and control
  7. Introduction to car vision
  8. Introduction to autonomous marine vehicles

Sincerely yours

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 to

the CVML email list, following instructions in