[visionlist] Invitation for the 2019 Short course on Autonomous Systems (self-driving cars), 26-27th August 2019, Aristotle University of Thessaloniki, Greece

ioannakoroni at csd.auth.gr ioannakoroni at csd.auth.gr
Thu May 16 07:13:17 -04 2019


Dear Autonomous Systems (cars) engineers, scientists and enthousiasts,

 

you are welcomed to register in the  short course on Autonomous Systems
having focus on autonomous/self-driving cars. 

It will take place on 26-27/8/2019 at the Aristotle University of
Thessaloniki, Thessaloniki, Greece.

 

The short course consists of 16 1-hour lectures organized 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, Motion estimation, Mapping and Localization.)
They also provide an overview of the State-of-the-Art on autonomous car
vision and real-time road infrastructure monitoring. 

Part B lectures provide an in-depth view of machine learning related topics
(Introduction to neural networks, Multilayer NNs/backpropagation, Deep
neural networks, Convolution NNs, Deep learning for target detection). They
will also cover Deep NN computation optimization schemes based on parallel
architectures, GPU programming, and fast convolution algorithms.
Furthermore, deep learning for 2D target (e.g., car, pedestrian) detection,
tracking and 3D target localization will be detailed. Finally, additional
topics related to autonomous car technologies, mainly focusing on car vision
will be presented, involving road scene understanding and 3D road modeling.

You can use the following link for course registration:

http://icarus.csd.auth.gr/dl-and-cv-for-autonomous-cars-2019/

 

For questions, please contact: Ioanna Koroni <ioannakoroni at csd.auth.gr
<mailto:ioannakoroni at csd.auth.gr> >

 

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).

 

Dr. R. Fan, Hong Kong University of Science and Technology (HKUST) will
overview work on self-driving cars, while also presenting progress in the
HKUST autonomous vehicle project.

 

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. 

 

Course participants may also want to register (if so desired) in a  second
back2back programming short course and hands-on workshop on Autonomous
Systems/Drones (28-30th August 2019) that will be announced separately and
will be open for registration very soon:

http://icarus.csd.auth.gr/drone-school-2019/

offering a mix of lectures and programming workshops (hands-on lab
exercises) and aiming at developing registrants' programming skills 

for  Deep Learning and Computer Vision, with focus on drone planning/control
and imaging. 

 

Relevant links:

1.	Prof. I. Pitas:
<https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el>
https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el
2.	H2020 project Multidrone:  <https://multidrone.eu/>
https://multidrone.eu/

 

 

Course description

Part A (8 hours), Computer vision topic list

1.           Introduction to autonomous systems imaging

2.           Introduction in computer vision

3.           Image acquisition, camera geometry

4.           Stereo and Multiview imaging

5.           Motion estimation

6.           Mapping and localization

7.            Introduction to autonomous car vision

8.             Real-time road infrastructure monitoring 

Part B (8 hours) Deep learning topic list

1.            Introduction to neural networks. Perceptron, backpropagation

2.            Deep neural networks. Convolutional NNs

3.            Parallel GPU and multicore CPU architectures. GPU programming

4.            Fast convolution algorithms

5.            Deep learning for target detection

6.            2D Target tracking and 3D target localization

7.            Road scene understanding

8.             3D road surface modelling

 

Sincerely yours

Prof. I. Pitas

Short course organizer

 


 
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