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Short course on Deep Learning and Computer Vision for autonomous systems


2020-11-18 - 2020-11-19 ( )


Tuition fees:
Program Director:
Ioannis Pitas

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Short course on Deep Learning and Computer Vision for autonomous systems

Form Submission is completed on



  • Short Description


    The Center for Education and Lifelong Learning of the Aristotle University of Thessaloniki welcomes you to the “Short course on Deep Learning and Computer Vision for autonomous systems, a 16-hour online course via zoom application.

    The Director of the Programme is Ioannis Pitas, Professor, School of Informatics, AUTh.

    Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki (AUTH), Greece. Since 1994, he has been a Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab. He served as a Visiting Professor at several Universities.

    His current interests are in the areas of computer vision, machine learning, autonomous systems, intelligent digital media, image/video processing, human-centred computing, affective computing, 3D imaging and biomedical imaging. He has published over 1000 papers, contributed in 47 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past, he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 70 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 42 such projects. Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: He is AUTH principal investigator in H2020 R&D projects Aerial Core and AI4Media. He is chair of the Autonomous Systems Initiative He is head of the EC funded AI doctoral school of Horizon2020 EU funded R&D project AI4Media (1 of the 4 in Europe). He has 31600+ citations to his work and h-index 85+ (Google Scholar).

    Start Date: 18/11/2020

    End of the course: 19/11/2020

    Duration: 16 hours

    The participants will receive a Certificate of attendance.

    Applications are submitted online from 13/10/2020 to 18/11/2020


    Aim and objectives

    The aim of this course is to provide useful knowledge on topics related to “Deep learning” & “Computer Vision” to young scientists.


    Participant selection & Requirements

    Priority order will be observed based on filing date up to 40 people.

    The course aims at young professionals and academics.


    • Mathematical background
    • Internet access



    E-learning education


    Course Description

    Ιntroduction to autonomous systems imaging, Introduction in computer vision, Image acquisition, camera geometry, Stereo and Multiview imaging, Motion estimation, Mapping and localization, 2D Target tracking and 3D target localization, Introduction to neural networks. Perceptron, backpropagation, Deep neural networks. Convolutional NNs, Parrarel GPU and multicore CPU architectures. GPU programming, Fast convolutions, Deep learning for target detection, Generative adversarial networks.

    More information:

    Educational Material:

    • PDF slides will be available to course attendees

    Lectures will be prerecorded to facilitate attendees in case they experience problems due to time difference.



    Upon completion of the course, participants will be awarded a Certificate of attendance.

    For the successful completion of the programme, the participants should:

    A) have attended all the teaching units. Absences may not exceed 10% of the scheduled training hours.

    B) to have paid all the tuition fees by 18/11/2020.


    Participation fees

    Early registration (till 30/10/2020):                200€ students, 300€ standard

    Registration (after 30/10/2020):                    250€ students, 350€ standard



    For further information, please contact with Mrs. Koroni Ioanna at

  • Contact

    For further information, please contact with Mrs. Koroni Ioanna at

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