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Dr Mandlenkosi Gwetu

Mandla Gwetu   
Dr Gwetu’s research areas include Computer Vision, Image Processing, Pattern Recognition and Machine Learning; with particular emphasis on datasets in the Biometric and Medical Imaging domains. His lecturing assignments encompass Advanced Programming, Artificial Intelligence and Deep Learning.

He has published and reviewed work in several accredited Computer Science journals as well as international and national conference proceedings. He has graduated several MSc students and is currently looking for potential MSc, PhD and Postdoc students who are interested in his line of research.
     
  Quote:   “Deep learning bares great prospects when practiced by the human mind.”
     
 Position:   Senior Lecturer
Qualification:   PhD (Computer Science)
MSc (Computer Science)
BSc (Mathematics & Computer Science)
     
Telephone:   033 260 5650
Email:
  gwetum@ukzn.ac.za
     
Recent Areas:   Computer Vision, Image Processing, Pattern Recognition, Deep Learning, Machine Learning, Medical Imaging
     
Recent Publications:   M.V. Gwetu, J-R. Tapamo, S. Viriri. Exploring the Impact of Purity Gap Gain on the Efficiency and Effectiveness of Random Forest Feature Selection. Springer Lecture Notes, September 2019.

A.S.P. Mlaba, M.V. Gwetu, S. Viriri. A Distance-based Approach to Modelling Reference Signature for Verification. Presented at ICTAS, March 2017.

M.V. Gwetu, J-R. Tapamo, S. Viriri. Segmentation of Retinal Blood Vessels using Normalized Gabor Filters and Automatic Thresholding. South African Computer Journal, December 2014.


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