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Biography

Saghir Alfasly received the Ph.D. degree in Information and Communication Engineering from the School of Electronic and Information Engineering, South China University of Technology, in 2020. Currently, he is a Postdoctoral Research Fellow with Shenzhen Key Laboratory of Advanced Machine Learning and Applications, and the Guangdong Key Laboratory of Intelligent Information Processing, College of Mathematics and Statistics, Shenzhen University. His current research interests include video understanding, action recognition, and machine learning.

I have worked in academia and industry on computer vision and machine learning applications, where my experience includes image/video understanding, multimodal learning, video-to-video summarization, and surveillance video analysis, using Python and C++ with the following deep learning frameworks: Pytorch, MxNet, Tensorflow, Keras, and Caffe.

Activities

Employment (2)

Mayo Clinic: Rochester, Minnesota, US

2023-04-24 to present | Research Fellow (Dept. Artificial Intelligence & Informatics)
Employment
Source: Self-asserted source
Saghir Alfasly

Shenzhen University: Shenzhen, Guangdong, CN

2020-11-01 to 2023-04-15 | PostDoc Research Fellow
Employment
Source: Self-asserted source
Saghir Alfasly

Education and qualifications (4)

South China University of Technology: Guangzhou, Guangdong, CN

2016-09-01 to 2020-08-01 | Ph.D (Information and Communication Engineering)
Education
Source: Self-asserted source
Saghir Alfasly

Kuvempu University: Shankaraghatta, Karnataka, IN

2014-08-01 to 2015-11-01 | Post Graduate Diploma in Human Resource Management (Management)
Qualification
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Saghir Alfasly

Kuvempu University: Shankaraghatta, Karnataka, IN

2013-08-01 to 2015-05-31 | M.Sc (Computer Science )
Education
Source: Self-asserted source
Saghir Alfasly

Sana'a University: Sana'a, Sana'a, YE

2006-09-01 to 2010-05-30 | Bachelor (Computer Science)
Education
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Saghir Alfasly

Professional activities (3)

IEEE: Shenzhen, Guangdong, CN

2021-01-01 to present | IEEE Member
Membership
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Saghir Alfasly

IEEE Signal Processing Society SPS: Guangzhou, Guandong, CN

2019-03-09 to 2020-12-30 | Student
Membership
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Saghir Alfasly

IEEE: Guangzhou, Guandong, CN

2019-03-07 to 2020-12-30 | Graduate Student
Membership
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Saghir Alfasly

Works (7)

OSRE: Object-to-Spot Rotation Estimation for Bike Parking Assessment

IEEE Transactions on Intelligent Transportation Systems
2024 | Journal article
Contributors: Saghir Alfasly; Zaid Al-Huda; Saifullahi Aminu Bello; Ahmed Elazab; Jian Lu; Chen Xu
Source: check_circle
Crossref

Auxiliary audio–textual modalities for better action recognition on vision-specific annotated videos

Pattern Recognition
2024-12 | Journal article
Contributors: Saghir Alfasly; Jian Lu; Chen Xu; Yu Li; Yuru Zou
Source: check_circle
Crossref

An Effective Video Transformer With Synchronized Spatiotemporal and Spatial Self-Attention for Action Recognition

IEEE Transactions on Neural Networks and Learning Systems
2024-02 | Journal article
Contributors: Saghir Alfasly; Charles K. Chui; Qingtang Jiang; Jian Lu; Chen Xu
Source: check_circle
Crossref

Learnable Irrelevant Modality Dropout for Multimodal Action Recognition on Modality-Specific Annotated Videos

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2022-06-21 | Conference paper
Contributors: Saghir Alfasly
Source: Self-asserted source
Saghir Alfasly

Auto-Zooming CNN-Based Framework for Real-Time Pedestrian Detection in Outdoor Surveillance Videos

IEEE Access
2019 | Journal article
Contributors: Saghir Alfasly; Beibei Liu; Yongjian Hu; Yufei Wang; Chang-Tsun Li
Source: check_circle
Crossref

Multi-Label-Based Similarity Learning for Vehicle Re-Identification

IEEE Access
2019 | Journal article
Contributors: Saghir Alfasly; Yongjian Hu; Haoliang Li; Tiancai Liang; Xiaofeng Jin; Beibei Liu; Qingli Zhao
Source: check_circle
Crossref

Variational Representation Learning for Vehicle Re-Identification

2019 IEEE International Conference on Image Processing (ICIP)
2019-08-26 | Conference paper
Source: Self-asserted source
Saghir Alfasly