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Skin Lesion Segmentation Using Local Binary Convolution-Deconvolution Architecture
2020
Image Analysis and Stereology
Deep learning techniques such as Deep Convolutional Networks have achieved great success in skin lesion segmentation towards melanoma detection. The performance is however restrained by distinctive and challenging features of skin lesions such as irregular and fuzzy border, noise and artefacts presence and low contrast between lesions. The methods are also restricted with scarcity of annotated lesion images training dataset and limited computing resources. Recent research in convolutional
doi:10.5566/ias.2397
fatcat:visogxzftngpvdocxtkwzei3oe