Automatic skin lesion segmentation using attention residual U-Net with improved encoder-decoder architecture

Rajdeep Kaur; Sukhjeet Kaur

doi:10.1007/s11042-024-18895-5

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Automatic skin lesion segmentation using attention residual U-Net with improved encoder-decoder architecture

Rajdeep Kaur Sukhjeet Kaur

Year: 2024 Journal: Multimedia Tools and Applications Vol: 84 (8)Pages: 4315-4341 Publisher: Springer Science+Business Media

DOI: 10.1007/s11042-024-18895-5

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Keywords:

Computer science Segmentation Residual Encoder Architecture Artificial intelligence Skin lesion Net (polyhedron) Pattern recognition (psychology) Computer vision Algorithm Dermatology Medicine

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Cutaneous Melanoma Detection and Management

Health Sciences → Medicine → Oncology

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Digital Media Forensic Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Automatic skin lesion segmentation using attention residual U-Net with improved encoder-decoder architecture

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