Workshop Name:
Deep Learning in Automated Driving
Sergiu Nedevschi, TUCN

Location: DoubleTree by Hilton Hotel Cluj – City Plaza, "Beijing" Room (5th floor)

Abstract: This workshop represents an introduction in deep learning based solutions for driving assistance and automated driving applications. The workshop is based on the authors’ experience gain in several research projects carried out at TUCN dealing with perception tasks. The approached topics are how to build a framework for deep learning; deep learning based stereo reconstruction and image segmentation; deep convolutional features’ use in boosting based solutions.


  1. Robert Varga, Lessons learned from developing the Gödel Deep Learning library
  2. Vlad Miclea, Deep learning-based approaches for stereo reconstruction
  3. Andra Petrovai, Deep learning for semantic image segmentation
  4. Arthur Costea, Boosting over deep convolutional features for object detection


Workshop Name:
Bosch Student Workshop - Path Planning
Catalin Golban, BOSCH

Location: DoubleTree by Hilton Hotel Cluj – City Plaza, "Beijing" Room (5th floor)

Abstract: Video based driver assistance systems is a continuously growing field in automotive industry. Based on surround sensors such as radar, video and ultrasound, driver assistance systems sense and interpret the traffic scenes. They assist the driver in various driving situations and increase the driving comfort. In addition, driver assistance systems improve driving safety by supporting the driver in critical driving situations that require rapid and safe action. Gradually increasing performance will lead to automated driving solutions available in series cars in the upcoming years.

After an overview of Bosch activities in the video-based driver assistance systems and functions, the focus will be on a set of advanced video development topics .The workshop will present in detail and at tutorial level several advanced stereo video algorithmic methods developed by Bosch R&D engineers in collaboration with students and researchers from Cluj universities in the last years, highlighting the importance of such methods in the context of the growing automated driving industry and showing the beauty and the challenges that appear when putting such methods on embedded hardware running in the car.


  1. Catalin Golban, Intro and Engineering Center Cluj - overview
  2. Maghear Ovidiu, Path planing on narrow city roads
  3. Anca Foloba, Path planning in off road environments
  4. Lucian Cristea, Path planning - from traditional to deep learning methods