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pro vyhledávání: '"Sobh, Ibrahim"'
Deep neural networks (DNNs) have accomplished impressive success in various applications, including autonomous driving perception tasks, in recent years. On the other hand, current deep neural networks are easily fooled by adversarial attacks. This v
Externí odkaz:
http://arxiv.org/abs/2107.07449
Autor:
Kiran, B Ravi, Sobh, Ibrahim, Talpaert, Victor, Mannion, Patrick, Sallab, Ahmad A. Al, Yogamani, Senthil, Pérez, Patrick
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. This review summarises deep reinforcem
Externí odkaz:
http://arxiv.org/abs/2002.00444
Data scarcity is a bottleneck to machine learning-based perception modules, usually tackled by augmenting real data with synthetic data from simulators. Realistic models of the vehicle perception sensors are hard to formulate in closed form, and at t
Externí odkaz:
http://arxiv.org/abs/1911.10575
3D semantic scene labeling is a fundamental task for Autonomous Driving. Recent work shows the capability of Deep Neural Networks in labeling 3D point sets provided by sensors like LiDAR, and Radar. Imbalanced distribution of classes in the dataset i
Externí odkaz:
http://arxiv.org/abs/1906.10964
In the autonomous driving domain, data collection and annotation from real vehicles are expensive and sometimes unsafe. Simulators are often used for data augmentation, which requires realistic sensor models that are hard to formulate and model in cl
Externí odkaz:
http://arxiv.org/abs/1905.07290
Autor:
Uricar, Michal, Krizek, Pavel, Hurych, David, Sobh, Ibrahim, Yogamani, Senthil, Denny, Patrick
Generative Adversarial Networks (GAN) have gained a lot of popularity from their introduction in 2014 till present. Research on GAN is rapidly growing and there are many variants of the original GAN focusing on various aspects of deep learning. GAN a
Externí odkaz:
http://arxiv.org/abs/1902.03442
Autor:
Talpaert, Victor, Sobh, Ibrahim, Kiran, B Ravi, Mannion, Patrick, Yogamani, Senthil, El-Sallab, Ahmad, Perez, Patrick
Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind's AlphaGo. It has been successfully deployed in commercial vehicles like Mobileye's path planning system. However, a vast m
Externí odkaz:
http://arxiv.org/abs/1901.01536
Autor:
Sobh, Ibrahim M., Darwish, Nevin M.
Motivated by recent advance of machine learning using Deep Reinforcement Learning this paper proposes a modified architecture that produces more robust agents and speeds up the training process. Our architecture is based on Asynchronous Advantage Act
Externí odkaz:
http://arxiv.org/abs/1804.05120
Autor:
ERAQI, HESHAM M.1, SOBH, IBRAHIM2
Publikováno v:
Communications of the ACM. Apr2021, Vol. 64 Issue 4, p64-66. 3p. 3 Color Photographs.
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