Temitope Mapayi
Tshwane University of Technology
39 Papers
76 Citations
Temitope Mapayi is an academic researcher from Tshwane University of Technology. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 7, co-authored 36 publications. Previous affiliations of Temitope Mapayi include Mangosuthu University of Technology & University of KwaZulu-Natal.
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Papers
Adaptive Thresholding Technique for Retinal Vessel Segmentation Based on GLCM-Energy Information
TL;DR: A local adaptive thresholding technique based on gray level cooccurrence matrix- (GLCM-) energy information for retinal vessel segmentation is presented and is time efficient with a higher average sensitivity and average accuracy rates in the same range of very good specificity.
Retinal Vessel Segmentation: A Comparative Study of Fuzzy C-means and Sum Entropy Information on Phase Congruency
TL;DR: An investigatory study on the combination of phase congruence with fuzzy c-means and the combination with gray level co-occurrence (GLCM) matrix sum entropy for the segmentation of retinal vessels.
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Automatic retinal vessel detection and tortuosity measurement
TL;DR: In this article, the combination of difference image and K-means clustering was used for the segmentation of retinal vessels, where stationary points in the vessel centerlines were used to model the detection of twists in the vessels segments.
Smart Hat for the blind with Real-Time Object Detection using Raspberry Pi and TensorFlow Lite
Matshehla Konaite,Pius A. Owolawi,Temitope Mapayi,Vusi Malele,Kehinde O. Odeyemi,Gbolahan Aiyetoro,Joseph Sunday Ojo +6 more
- 09 Dec 2021
TL;DR: In this paper, the authors used the combination of working aid blind techniques to help blind people to have better navigation against objects, also to be aware of road and traffic lights signs using real-time image processing.
22
Interactive IoT-based Speech-Controlled Home Automation System
Nombulelo Cc Noruwana,Pius A. Owolawi,Temitope Mapayi +2 more
- 25 Nov 2020
TL;DR: In this paper, the authors presented the development of an interactive Internet of Things (IoT) based Speech-Controlled Home Automation system using Google Assistant, which is an interactive home automation, or commonly known as smart house system, enabling users to control their home electrical appliances remotely with voice-based speech recognition through a mobile devices using a Google infrastructure known as Google Assistant.
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