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An Efficient Ensemble of Deep Neural Networks for Detection and Classification of Diabetic Foot Ulcers Images

Authors:
Basabi Chakraborty
Suma Sailaja Nakka
Takahisa Sanada

Keywords: Diabetic foot ulcers classification, deep neural network, ensemble classifier

Abstract:
Classification of Diabetic Foot Ulcers (DFU) wounds using computerized methods is becoming an important research area due to development of machine learning and deep learning algorithms for image classification. In this work an efficient ensemble of several deep neural networks has been proposed for classification of DFU images. Simulation experiments with publicly available Diabetic Foot Ulcers Grand Challenge (DFUC 2021) data set has been done to justify the proposal. The performance of the ensemble has been studied and it is found that the ensemble produced a classification accuracy of 91% with a reasonable computational cost which is considered higher compared to the existing approaches.

Pages: 48 to 49

Copyright: Copyright (c) IARIA, 2023

Publication date: March 13, 2023

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-68558-056-8

Location: Barcelona, Spain

Dates: from March 13, 2023 to March 17, 2023