no code implementations • 15 Jul 2021 • Ibrahim Sobh, Ahmed Hamed, Varun Ravi Kumar, Senthil Yogamani
On the other hand, current deep neural networks are easily fooled by adversarial attacks.
no code implementations • 2 Feb 2020 • B Ravi Kiran, Ibrahim Sobh, Victor Talpaert, Patrick Mannion, Ahmad A. Al Sallab, Senthil Yogamani, Patrick Pérez
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.
no code implementations • 24 Nov 2019 • Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Mohamed Shawky
Evaluation is performed on unseen real LiDAR frames from KITTI dataset, with different amounts of simulated data augmentation using the two proposed approaches, showing improvement of 6% mAP for the object detection task, in favor of the augmenting LiDAR point clouds adapted with the proposed neural sensor models over the raw simulated LiDAR.
no code implementations • 26 Jun 2019 • Mohammed Abdou, Mahmoud Elkhateeb, Ibrahim Sobh, Ahmad El-Sallab
Imbalanced distribution of classes in the dataset is one of the challenges that face 3D semantic scene labeling task.
1 code implementation • 17 May 2019 • Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Nader Essam
Simulators are often used for data augmentation, which requires realistic sensor models that are hard to formulate and model in closed forms.
no code implementations • 9 Feb 2019 • Michal Uricar, Pavel Krizek, David Hurych, Ibrahim Sobh, Senthil Yogamani, Patrick Denny
Generative Adversarial Networks (GAN) have gained a lot of popularity from their introduction in 2014 till present.
no code implementations • 6 Jan 2019 • Victor Talpaert, Ibrahim Sobh, B Ravi Kiran, Patrick Mannion, Senthil Yogamani, Ahmad El-Sallab, Patrick Perez
Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind's AlphaGo.
no code implementations • 10 Oct 2018 • Ibrahim Sobh, Loay Amin, Sherif Abdelkarim, Khaled Elmadawy, Mahmoud Gamal Saeed, Omar Abdeltawab, Mostafa Gamal, Ahmad El Sallab
In this paper, we present a novel framework for urban automated driving based on multi-modal sensors; LiDAR and Camera.