Classification and Detection of Cyanosis Images on Lightly and Darkly Pigmented Individual Human Skins using a Fine-Tuned MobileNet Architecture

Lukoki Mpova, Thokozani Shongwe, Ali Hasan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The classification and detection of cyanosis using in-vivo and in-silico image processing approaches are intriguing and very special. In this study, a peripheral and central cyanosis image classification approach, using lightweight-deep learning Convolutional Neural Networks (CNNs), referred to as pre-trained MobileNet architecture, was introduced. This modified MobileNet model was assessed using the sanctioned dataset of 1300-image collected from multiple cyanosis published datasets. The augmentation technique was applied on the training dataset to enrich the productivity. Emphatic results, validation-accuracy and accuracies on the training and test datasets of 95% and 97%, respectively; were obtained as compared to the validation-accuracy of 79% and 82% of the Simple Convolutional Neural Networks (SCNNs) and Fine-tuned VGG16 models attained from prior stud.

Original languageEnglish
Title of host publication6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings
EditorsSameerchand Pudaruth, Upasana Singh
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350314809
DOIs
Publication statusPublished - 2023
Event6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Durban, South Africa
Duration: 3 Aug 20234 Aug 2023

Publication series

Name6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023 - Proceedings

Conference

Conference6th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, icABCD 2023
Country/TerritorySouth Africa
CityDurban
Period3/08/234/08/23

Keywords

  • Deep Learning
  • cyanosis
  • modified mobileNet model
  • pre-trained MobileNet model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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