Dear Machine Learning, Computer Vision and Autonomous Systems Engineers, Scientists and Enthusiasts,

you are welcomed to register and attend the Web e-Course  on Computer Vision consisting of the following two CVML Web e-Course Modules on offer (total 22 lectures):

Machine Learning  (12 Lectures), http://icarus.csd.auth.gr/machine-learning-web-module/

1)      Introduction to Machine Learning

2)      Data Clustering

3)      Distance-based Classification

4)      Decision Surfaces. Support Vector Machines

5)      Label Propagation

6)      Dimensionality Reduction

7)      Graph-based Dimensionality Reduction

8)      Kernel Methods

9)      Bayesian Learning

10)  Parameter Estimation

11)  Hypothesis Testing

12)  Syntactic Pattern Recognition

Neural Networks/Deep Learning (14 Lectures), http://icarus.csd.auth.gr/neural-networks-and-deep-learning-web-module/

1. Artificial Neural Networks. Perceptron
2. Multilayer Perceptron. Backpropagation.
3. Convolutional Neural Networks
4. 1D Convolutional Neural Networks
5. Deep Autoencoders
6. Attention and Transformer Networks
7. Recurrent Neural Networks. LSTMs
8. Deep Object Detection
9. Special topics in Object Detection
10. Few-Shot Object Recognition
11. Deep Semantic Image Segmentation
12. Adversarial Machine Learning
13. Generative Adversarial Networks in Multimedia Creation
14. Mathematical Brain Modeling

Around 50% of the lectures provide free access to the full lecture pdf!

You can find sample Web e-Course Module material to make up your mind and/or can perform CVML Web e-Course registration in:

http://icarus.csd.auth.gr/cvml-web-lecture-series/

For questions, please contact: Ioanna Koroni <koroniioanna@csd.auth.gr>

More information on this Web e-course: This Web e-Course Computer Vision material that can cover a semester course, but you can master it in approximately 1 month.

Course materials are at senior undergraduate/MSc level in a CS, CSE, EE or ECE or related Engineering or Science Department. Their structure, level and offer are completely different from what you can find in either Coursera or Udemy.

CVML Web e-Course Module materials typically consist of: a) a lecture pdf/ppt, b) lecture self-assessment understanding questionnaire and lecture video, programming exercises, tutorial exercises (for several modules/lectures)  and overall course module satisfaction questionnaire.

Asynchronous tutor support will be provided in case of questions.

Course materials have been very successfully used in many top conference keynote speeches/tutorials worldwide and in short courses, summer schools, semester courses delivered by AIIA Lab physically or on-line from 2018 onwards, attracting many hundreds of registrants.

More information on other CVML Web e-course: Several other Web e-Course Modules are  offered on Deep Learning, Computer Vision, Autonomous Systems, Signal/Image/Video Processing, Human-centered Computing, Social Media, Mathematical Foundations, CVML SW tools.

See: http://icarus.csd.auth.gr/cvml-web-lecture-series/

You can combine CVML Web e-Course Modules to create CVML Web e-Courses (typically consisting of 16 lectures) of your own choice that cater your personal education needs.

Each CVML Web e-Course you will create (typically 16 lectures) provides you material that can cover a semester course, but you can master it in approximately 1 month.

Academic/Research/Industry offer and arrangements

Special arrangements can be made to offer the material of these CVML Web e-Course Modules at University/Department/Company level:

• by granting access to the material to University/research/industry lecturers to be used as an aid in their teaching,
• by enabling class registration in CVML Web e-Courses
• by delivering such live short courses physically or on-line by Prof. Ioannis Pitas
• by combinations of the above.

The CVML Web e-Course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Coordinator of International AI Doctoral Academy (AIDA), past 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 has 34100+ citations to his work  and h-index 87+.

The informatics Department at AUTH ranked 106th internationally in the field of Computer Science for 2019 in the Leiden Ranking list

Relevant links:

1. Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
2. International AI Doctoral Academy (AIDA): https://www.i-aida.org/
3. Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/
4. Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/
5. Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/
6. AIIA Lab: https://aiia.csd.auth.gr/

Sincerely yours

Prof. I. Pitas

Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab)

Aristotle University of Thessaloniki, Greece