Congratulations, Dr Burhan!
Dr Burhan Rashid Hussein passed his viva in November with his research, Segmentation and Species Identification for Digitized Herbarium Specimen Images Using Computer Vision and ML Techniques.
Dr Burhan Rashid Hussein joined UBD in 2018 and recently passed his viva on 6th November 2021 with his research, Segmentation and Species Identification for Digitized Herbarium Specimen Images Using Computer Vision and Machine Learning Techniques under the supervision of Dr Owais Malik and Dr Ong Wee Hong.
His most notable work is titled, Automated Extraction of Phenotypic Leaf Traits of Individual Intact Herbarium Leaves from Herbarium Specimen Images Using Deep Learning Based Semantic Segmentation, published at Sensors 2021, 21(13), 4549; https://doi.org/10.3390/s21134549
Under his doctoral research programme, he has published in the following papers:
Application of Computer Vision and Machine Learning for Digitized Herbarium Specimens: A Systematic Literature Review. BR Hussein, OA Malik, WH Ong, JWF Slik arXiv preprint arXiv:2104.08732, 2021
Reconstruction of damaged herbarium leaves using deep learning techniques for improving classification accuracy. BR Hussein, OA Malik, WH Ong, JWF Slik Ecological Informatics 61, 101243, 2021
Automated Extraction of Phenotypic Leaf Traits of Individual Intact Herbarium Leaves from Herbarium Specimen Images Using Deep Learning Based Semantic Segmentation. BR Hussein, OA Malik, WH Ong, JWF Slik Sensors 21 (13), 4549, 2021
Semantic segmentation of herbarium specimens using deep learning techniques. BR Hussein, OA Malik, WH Ong, JWF Slik. Computational Science and Technology, 321-330, 2020
Automated classification of tropical plant species data based on machine learning techniques and leaf trait measurements. BR Hussein, OA Malik, WH Ong, JWF Slik Computational Science and Technology, 85-94
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