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DimensionsR, Ezhilan and D, Vinod Kumar and P, Umasankar and Suman, Sukhavasi and G, Murali and P, Kowsalikanand (2024) Optimizing Diabetic Foot Ulcer Classification with Transfer Learning: A Performance Analysis. In: UNSPECIFIED.
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Official URL: https://doi.org/10.1109/I-SMAC61858.2024.10714832
Abstract
Diabetic foot ulcers (DFUs) are common in diabetes due to neuropathy and poor circulation, risking severe complications. This study presents a DFU classification approach using transfer learning models: ResNet152, EfficientNetB7, and SE-ResNeXt. EfficientNetB7 achieved highest accuracy (99.65%) and sensitivity (99.8%). ResNet152 had highest specificity (99.8%). Results highlight transfer learning's efficacy for DFU detection, improving diagnostic accuracy and patient outcomes.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Computer Science > Artificial Intelligence Computer Science > Computer Science Applications Computer Science > Information Systems and Management Computer Science > Computer Networks and Communications Computer Science > Computer Vision and Pattern Recognition Social Sciences > Social Sciences (miscellaneous) |
| Divisions: | Medicine > Aarupadai Veedu Medical College and Hospital, Puducherry, India > Dermatology |
| Depositing User: | Unnamed user with email techsupport@mosys.org |
| Last Modified: | 27 Nov 2025 06:46 |
| URI: | https://ir.vmrfdu.edu.in/id/eprint/1777 |
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