142 citations · 452 across the 57 of their papers we have counts for
3 papers · 2 filters
Deep Semantic Segmentation for Automated Driving: Taxonomy, Roadmap and Challenges
Mennatullah Siam, Sara Elkerdawy, Martin Jagersand +1
Semantic segmentation was seen as a challenging computer vision problem few years ago. Due to recent advancements in deep learning, relatively accurate solutions are now possible f…
Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework
B Ravi Kiran, Arindam Das, Senthil Yogamani
Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult…
Deep Reinforcement Learning framework for Autonomous Driving
Ahmad El Sallab, Mohammed Abdou, Etienne Perot +1
Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despi…