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RVIP 2023 : Summer School on Robotics and Visual Information Processing

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Link: https://rvip.mik.uni-pannon.hu
 
When Jul 3, 2023 - Jul 13, 2023
Where Veszprem, Hungary
Submission Deadline Jun 15, 2023
Categories    robotics   brain imaging   computer vision   gpu
 

Call For Papers

Take part in our Summer School on Robotics and Visual Information Processing! During the time you spend with us, you will not only get a glimpse of the modern IT solutions from the fields of robotics, machine vision, and brain imaging, but you will also be able to try them out in the context of group project tasks.

Requirements
The ideal participant has past the second semester of his/her computer science (or a closely related field) BSc studies and has basic programming and math skills. Elementary knowledge of signal and/or image processing is an advantage, but not required.

Aim
Giving tutorials from the elements to some high-level concepts in the field of robotics and visual information processing. Learn the latest state-of-art research results from internationally acknowledged speakers. Feel the culturally rich atmosphere of the historic town of Veszprém during the summer programs of the European Capital of Culture.

Scope
GPU programming: Introduction to parallel computing and the GPU architecture, the basics of GPU programming and parallel algorithms, case studies of GPU accelerated applications including numerical simulation, image processing, data analysis.

Brain Imaging: Introduction to the fundamentals of brain imaging technologies (CT, MRI, PET, EEG). The electrophysiological basis of EEG, introduction to signal processing and the analysis of EEG signals, fundamentals of Brain Computer Interfaces.

Robotics: Basic coordinate geometry behind robotics: rotation, homogeneous transformations. Mobile robotics: kinematics, localization, mapping, navigation. A general introduction to the kinematics of robot manipulators. Robot programming.

Computer Vision: Basic concepts of computer vision including camera models, camera calibration, pose estimation. Low-level and semantic approaches for image segmentation, object recognition, and anomaly detection.

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