Article

Advancing skin cancer diagnosis with a multi‐branch ShuffleNet architecture

2024-03-01

Abstract excerpt

Abstract In this study, we present an innovative approach for enhancing skin cancer classification through a multi‐branch architecture inspired by ShuffleNet. Our methodology focuses on improving feature extraction and representation, emphasizing cross‐channel information exchange to achieve superior accuracy. The architecture comprises three branches: a primary feature enhancement branch, a parallel feature enhan...

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Literature Corpus work: 5d787321-e0d3-5786-b3e6-bdea9d029d61
DOI: 10.1002/ima.23051

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