Squeeze-MNet: Precise Skin Cancer Detection Model for Low Computing IoT Devices Using Transfer Learning

Squeeze-MNet: Precise Skin Cancer Detection Model for Low Computing IoT Devices Using Transfer Learning

Cancer remains a deadly disease. We developed a lightweight, accurate, general-purpose deep learning algorithm for skin cancer classification. Squeeze-MNet combines a Squeeze algorithm for digital hair removal during preprocessing and a MobileNet deep learning model with predefined weights. The Sque...

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Bibliographic Details
Main Authors: Rupali Kiran Shinde, Md. Shahinur Alam, Md. Biddut Hossain, Shariar Md Imtiaz, JoonHyun Kim, Anuja Anil Padwal, Nam Kim
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Cancers
Subjects:
transfer learning
malignant
IoT
MobileNet
squeezed dataset
AUC-ROC
Online Access:https://www.mdpi.com/2072-6694/15/1/12

Internet

https://www.mdpi.com/2072-6694/15/1/12

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