Progressive Weighted Self-Training Ensemble for Multi-Type Skin Lesion Semantic Segmentation

In this study, we propose the Progressive Weighted Self-training Ensemble (PWStE) method that reinforces efficiency of labeled data for multi-type skin lesion semantic segmentation. The generation of multi-type skin lesion labeled data is extremely expensive as it should only be performed by dermato...

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Bibliografske podrobnosti

Principais autores:	Cheolwon Lee, Sangwook Yoo, Semin Kim, Jongha Lee
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2022-01-01
Serija:	IEEE Access
Teme:	Deep learning ensemble multi-type skin lesion semi-supervised learning semantic segmentation
Online dostop:	https://ieeexplore.ieee.org/document/9953982/
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