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Found 3 papers, 1 papers with code
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion Segmentation
The computer-aided diagnosis (CAD) of skin diseases relies heavily on automated skin lesion segmentation, albeit presenting considerable challenges due to lesion diversity in shape, size, color, and texture, as well as potential blurry boundaries with surrounding tissues.
Swin-Tempo: Temporal-Aware Lung Nodule Detection in CT Scans as Video Sequences Using Swin Transformer-Enhanced UNet
However, identifying lung nodules poses significant challenges for radiologists, who rely heavily on their expertise for accurate diagnosis.
SWP-LeafNET: A novel multistage approach for plant leaf identification based on deep CNN
According to a comparative analysis, the suggested approach is more accurate than hand-crafted feature extraction methods and other deep learning techniques in terms of 99. 67% and 99. 81% accuracy.
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