| Deep reinforcement learning for autonomous driving: A survey BR Kiran, I Sobh, V Talpaert, P Mannion, AA Al Sallab, S Yogamani, ... IEEE Transactions on Intelligent Transportation Systems 23 (6), 4909-4926, 2021 | 1927 | 2021 |
| Exploring applications of deep reinforcement learning for real-world autonomous driving systems V Talpaert, I Sobh, BR Kiran, P Mannion, S Yogamani, A El-Sallab, ... VISAPP: International Conference on Computer Vision Theory and Applications, 2019 | 90 | 2019 |
| Yes, we gan: Applying adversarial techniques for autonomous driving M Uricár, P Krizek, D Hurych, I Sobh, S Yogamani, P Denny arXiv preprint arXiv:1902.03442, 2019 | 62 | 2019 |
| End-to-end multi-modal sensors fusion system for urban automated driving I Sobh, L Amin, S Abdelkarim, K Elmadawy, M Saeed, O Abdeltawab, ... | 59 | 2018 |
| LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving AE Sallab, I Sobh, M Zahran, N Essam ICML Workshop on AI for Autonomous Driving, 2019 | 49 | 2019 |
| An optimized dual classification system for Arabic extractive generic text summarization I Sobh, N Darwish, M Fayek Giza, Egypt, 2009 | 42 | 2009 |
| Yolo4d: A spatio-temporal approach for real-time multi-object detection and classification from lidar point clouds A El Sallab, I Sobh, M Zidan, M Zahran, S Abdelkarim | 32 | 2018 |
| Adversarial attacks on multi-task visual perception for autonomous driving I Sobh, A Hamed, VR Kumar, S Yogamani arXiv preprint arXiv:2107.07449, 2021 | 24 | 2021 |
| Deep reinforcement learning for autonomous driving: A survey. arXiv 2020 BR Kiran, I Sobh, V Talpaert, P Mannion, AAA Sallab, S Yogamani, ... arXiv preprint arXiv:2002.00444, 0 | 20 | |
| Unsupervised neural sensor models for synthetic lidar data augmentation AE Sallab, I Sobh, M Zahran, M Shawky arXiv preprint arXiv:1911.10575, 2019 | 16 | 2019 |
| Comparative study of neuro-evolution algorithms in reinforcement learning for self-driving cars A AbuZekry, I Sobh, ES Hemayed, M Hadhoud, M Fayek European Journal of Engineering Science and Technology 2 (4), 60-71, 2019 | 11 | 2019 |
| A trainable Arabic Bayesian extractive generic text summarizer I Sobh, N Darwish, M Fayek Proceedings of the Sixth Conference on Language Engineering ESLEC, 49-154, 2006 | 11 | 2006 |
| AA; Yogamani, S.; and Pérez BR Kiran, I Sobh, V Talpaert, P Mannion, A Sallab Deep reinforcement learning for autonomous driving: A survey, 2020, 2002 | 8 | 2002 |
| Statistical formant speech synthesis for Arabic A Jafri, I Sobh, A Alkhairy Arabian Journal for Science and Engineering 40, 3151-3159, 2015 | 7 | 2015 |
| End-to-end 3D-pointcloud semantic segmentation for autonomous driving M Abdou, M Elkhateeb, I Sobh, A Elsallab arXiv preprint arXiv:1906.10964, 2019 | 6 | 2019 |
| Evaluation Approaches for an Arabic Extractive Generic Text Summarization System I Sobh, N Darwish, M Fayek proceeding of 2nd International Conference on Arabic Language Resource and …, 2009 | 6 | 2009 |
| RL_QOptimizer: A Reinforcement Learning Based Query Optimizer M Ramadan, A El-Kilany, HMO Mokhtar, I Sobh IEEE Access 10, 70502-70515, 2022 | 5 | 2022 |
| End-to-end multitask learning for driver gaze and head pose estimation M Ewaisha, M El Shawarby, H Abbas, I Sobh Electronic Imaging 32, 1-6, 2020 | 5 | 2020 |
| End-to-End Framework for Fast Learning Asynchronous Agents I Sobh, N Darwish NIPS, 32nd Conference on Neural Information Processing Systems, Imitation …, 2018 | 4* | 2018 |
| Aspice applicability on new automotive technologies (ai) E Edwar, S Sameh, I Sobh European Conference on Software Process Improvement, 430-440, 2022 | 3 | 2022 |
Senthil YogamaniResearcher / Engineering Director, Data-centric AI for Autonomous Driving at Qualcomm IrelandVerified email at qualcomm.com
