For an online listing please see: Google Scholar | Semantic Scholar

PhD Student
CSIRO Data61
UOW AMRL VILA
School of Computing & IT
University of Wollongong
Current Office:
Room No. 3.237, Building 3
UOW Wollongong Campus
Contact me:
1 sr801uowmail.edu.au
2 saimun.rahmandata61.csiro.com
(+61) 4 1374 0811
Find me on :
•
•
•
•
Listing by: research areas | publication type
Thesis

Human Activity Recognition in Low Quality Videos Using Spatio-Temporal Features
M.Sc. (by Research) thesis
Multimedia University, Cyberjaya, June 2016
Preprints

Journal Papers

Deep Learning based HEp-2 Image Classification: A Comprehensive Review
Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou
Medical Image Analysis (2020):101764.

Exploiting textures for better action recognition in low-quality videos
Saimunur Rahman, John See and Chiung Ching Ho
EURASIP Journal on Image and Video Processing, 2017(1), p.74.

Deep CNN Object Features for Improved Action Recognition in Low Quality Videos
Saimunur Rahman, John See and Chiung Ching Ho
Advanced Science Letters, 23(11), pp.11360-11364
Conference Papers

ReDro: Efficiently Learning Large-sized SPD Visual Representation
Saimunur Rahman, Lei Wang, Changming Sun, Luping Zhou
European Conference on Computer Vision (ECCV), UK, 23-28 August 2020.



Leveraging Textural Features for Recognizing Actions in Low Quality Videos
Saimunur Rahman, John See and Chiung Ching Ho
International Conference on Robotics, Vision, Signal Processing & Power Applications (ROVISP), February 2-3, Penang, Malaysia, 2016


Action Recognition by Jointly using Shape, Motion and Texture Features in Low Quality Videos
Saimunur Rahman, John See and Chiung Ching Ho
IEEE International Conference on Signal and Image Processing Applications (ICSIPA), October 19-21, Kuala Lampur, Malaysia, 2015
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.
© 2018 Saimunur Rahmnan. CC-NC-SA-4.0. Built with Bootstrap v3.3.6. Style adopted from Animesh Garg.