Areas of Interest
Image Processing, Pattern Recognition and Machine learning
Nabeel Mohammed is currently working as an Assistant Professor within the Department of Computer Science and Engneering at University of Liberal Arts Bangladesh (ULAB). He completed his BSc in Computer Science from Monash Univesity, Australia. After his graduation he worked as a Software Engineer at Editure Ltd., a Melbourne-based software firm specialising in the K-12 market. After three and half years in the software industry, he went back to Monash to complete his PhD in Computer Science under the supervision of Dr. David Squire. His thesis work concentrated on the extraction and application of adaptively learnt image texture features.
He returned to Bangladesh after completing the PhD. He joined ULAB as an Assistant Professor at the Department of Computer Science and Engineering in January 2015.
Tasnim Sami, Nabeel Mohammed and Sifat Momen, Learning “initial feature weights” for CBIR using query augmentation, International Journal of Multimedia Information Retrieval, March 2016, Springer-Verlag (London), ISSN: 2192-6611 (print), ISSN: 2192-662X (online)
Mohammad Hossain, Nabeel Mohammed, and Rafi Md Najmus Sadat, “Chord to triangular arm angle (CTAA), a more accurate version of the CTAR corner detector,” in 2015 IEEE International Conference on Signal and Image Processing Applications (IEEE ICSIPA 2015), Kuala Lumpur, Malaysia,
Rafi Md Najmus Sadat, Asiful Hossain, Nabeel Mohammed, Naurin Afrin. Efficient and Reliable corner detectors through Analysing CPDA, In Proceedings of the Twentieth International Symposium on Artificial Life and Robotics 2015 (ISAROB, 2015), Beppu, Japan.
Nabeel Mohammed and David McG. Squire, An evaluation of sparseness as a
criterion for selecting independent component filters, when applied to
texture retrieval, In Proceedings of the International Conference on
Digital Image Computing: Techniques and Applications (DICTA 2014), NSW, Australia.
Nabeel Mohammed and Sohel Rana, Improved texture retrieval by combining different variants of Local Binary Patterns, In proceedings of the 8th International Conference on Electrical and Computer Engineering (ICECE 2014), Dhaka, Bangladesh.
Nabeel Mohammed and David McG. Squire, ICFSIFT: Improving collection-specific CBIR with ICF-based local features, In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA 2013), Hobart, Australia.
Nabeel Mohammed and David McG. Squire, Improved Texture Features for CBIR using Response Scaling and Locally Normalised Convolution, In Proceedings of the 11th International Workshop on Content-Based Multimedia Indexing, Veszprém, Hungary.
Nabeel Mohammed and David McG. Squire, Efficient and Accurate Independent Component Filter-based Features for Texure Similarity, In Proceedings of the 20th IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, September 15-18 2013.
Nabeel Mohammed and David McG. Squire, Effectiveness of ICF features for collection-specific CBIR, in Proceedings of the 9th International Workshop on Adaptive Multimedia Retrieval, Barcelona, Spain, number 7836 in Lecture Notes in Computer Science, pp. 83–95, Springer-Verlag
Nabeel Mohammed and David McG. Squire, An improved method for choosing effective Independent Component Filters for CBIR, In Proceedings of the 26th International Conference on Image and Vision Computing New Zealand, Auckland, New Zealand, pp. 517-522