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About Neural Architecture Search For Skin Lesion Classification
This document summarizes a research paper that used neural architecture search to develop a deep learning model for skin lesion classification. The researchers employed a hill-climbing search strategy along with network morphism operations to efficiently explore the search space and find a suitable network structure. The proposed approach was able to produce architectures that achieved similar results to manually designed networks, but using almost 20 times fewer parameters. The entire search process took on average only 18 hours on a single GPU. The researchers tested their approach on a practical medical dataset for malignant melanoma detection, which differs from typical benchmark datasets in terms of class balance, image quality and size.
Detailed Information
| Author: | ['z123'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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