Ibrahim Sobh
Impact in
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
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- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
Papers in
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- Robotic Path Planning Algorithms 2
- Video Surveillance and Tracking Methods 2
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- Adversarial Robustness in Machine Learning 2
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Senthil Yogamani (4 shared papers)Patrick Pérez (2 shared papers)Bangalore Ravi Kiran (2 shared papers)Patrick Mannion (2 shared papers)Ahmad El Sallab (2 shared papers)Michal Uřičář (1 shared paper)Patrick Denny (1 shared paper)Pavel Křížek (1 shared paper)
In The Last Decade
Ibrahim Sobh
14 papers receiving 151 citations
Peers
Comparison fields: 5 of 44
- Automotive Engineering 59
- Computer Vision and Pattern Recognition 77
- Computer Graphics and Computer-Aided Design 7
- Artificial Intelligence 54
- Structural Biology 2
Countries citing papers authored by Ibrahim Sobh
This map shows the geographic impact of Ibrahim Sobh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ibrahim Sobh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahim Sobh more than expected).
Fields of papers citing papers by Ibrahim Sobh
This network shows the impact of papers produced by Ibrahim Sobh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ibrahim Sobh. The network helps show where Ibrahim Sobh may publish in the future.
Co-authors
The 18 scholars most cited alongside Ibrahim Sobh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 33 | |
| 2 | End-To-End Multi-Modal Sensors Fusion System For Urban Automated Driving | 2018 | 27 |
| 3 | 2019 | 26 | |
| 4 | 2019 | 23 | |
| 5 | YOLO4D: A Spatio-temporal Approach for Real-time Multi-object Detection and Classification from LiDAR Point Clouds | 2018 | 18 |
| 6 | 2021 | 14 | |
| 7 | 2022 | 5 | |
| 8 | 2015 | 4 | |
| 9 | 2020 | 3 | |
| 10 | 2022 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2025 | 1 | |
| 14 | 2021 | 1 | |
| 15 | 2021 | 0 |
About Ibrahim Sobh
Ibrahim Sobh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Human-Computer Interaction and Computer Networks and Communications, having authored 15 papers that have together received 159 indexed citations. Recurring topics across this work include Gaze Tracking and Assistive Technology (3 papers), Autonomous Vehicle Technology and Safety (3 papers), Optimization and Search Problems (2 papers), Robotic Path Planning Algorithms (2 papers), Adversarial Robustness in Machine Learning (2 papers), Video Surveillance and Tracking Methods (2 papers), Traffic Prediction and Management Techniques (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Automotive Engineering (59 citations), Computer Vision and Pattern Recognition (77 citations), Computer Graphics and Computer-Aided Design (7 citations), Artificial Intelligence (54 citations) and Structural Biology (2 citations). Ibrahim Sobh has collaborated with scholars based in Egypt, France and Ireland. Frequent co-authors include Senthil Yogamani, Patrick Pérez, Bangalore Ravi Kiran, Patrick Mannion, Ahmad El Sallab, Michal Uřičář, Patrick Denny, Pavel Křížek, Varun Ravi Kumar and Mahmoud S. R. Saeed. Their work appears in journals such as IEEE Access, Journal of Imaging Science and Technology, Arabian Journal for Science and Engineering, Neural Computing and Applications and Communications of the ACM.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.