Mohamed Elhoseiny

41 papers and 1.2k indexed citations i.

Mohamed Elhoseiny is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Mohamed Elhoseiny has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 22 papers in Artificial Intelligence and 4 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Mohamed Elhoseiny’s work include Multimodal Machine Learning Applications (23 papers), Domain Adaptation and Few-Shot Learning (16 papers) and Human Pose and Action Recognition (8 papers). Mohamed Elhoseiny is often cited by papers focused on Multimodal Machine Learning Applications (23 papers), Domain Adaptation and Few-Shot Learning (16 papers) and Human Pose and Action Recognition (8 papers). Mohamed Elhoseiny collaborates with scholars based in Saudi Arabia, United States and Canada. Mohamed Elhoseiny's co-authors include Abduallah Mohamed, Kun Qian, Christian Claudel, Ivan Skorokhodov, Marcus Rohrbach, Ahmed Elgammal, Sergey Tulyakov, Jun Chen, Marc’Aurelio Ranzato and Arslan Chaudhry and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).