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Impact Factor : 8.14

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Paper Title: REAL TIME DIABETIC FOOT ULCER DETECTION ON MOBILE PLATFORMS VIA DEEP LEARNING
Authors Name: Nishant Raj Sharma , Suja Sangtam , Dr N Rajkumar
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IJRTI_201662
Published Paper Id: IJRTI2504241
Published In: Volume 10 Issue 4, April-2025
DOI:
Abstract: —Diabetic foot ulcers (DFU) are a common and serious complication in individuals with diabetes, and early detection plays a crucial role in effective treatment and prevention of further complications. Automated DFU Detection and Classification using Deep learning (DL) refers to the application of deep learning techniques to automatically detect and classify diabetic foot ulcers from medical images. DL, a subfield of machine learning, has shown promising results in medical imaging analysis, including diabetic foot ulcer detection. The use of deep learning in DFU detection provides various benefits, including the ability to learn complex features, adaptability to different image modalities, and the potential for high accuracy in detection and classification tasks. Therefore, this article introduces a novel sparrow search optimization (SSO) with deep learning enabled diabetic foot ulcer detection and classification (SSODLDFUDC) technique. The presented SSODL-DFUDC technique’s goal lies in identifying and classifying DFU. The proposed technique employs the Inception-ResNet-v2 model for feature vector generation to accomplish this. Since the trial and error manual hyperparameter tuning of the Inception-ResNet-v2 model is a tedious and erroneous process, the SSO algorithm can be used for the optimal hyperparameter selection of the Inception-ResNetv2 model which in turn enhances the overall DFU classification results. Moreover, the classification of DFU takes place using the stacked sparse autoencoder (SSAE) model. The comprehensive experimental outcomes demonstrate the improved performance of the SSODL-DFUDC system related to existing DL techniques.
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Cite Article: "REAL TIME DIABETIC FOOT ULCER DETECTION ON MOBILE PLATFORMS VIA DEEP LEARNING", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c146-c150, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504241.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2504241
Registration ID:201662
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: c146-c150
Country: Chennai, Tamil Nadu, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504241
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504241
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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