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Melanoma skin cancer is the most life‐threatening and fatal disease among the family of skin cancer diseases. Modern technological developments and research methodologies made it possible to detect and identify this kind of skin cancer more effectively; however, the automated localization and segmentation of skin lesion at earlier stages is still a challenging task due to the low contrast between melanoma moles and skin portion and a higher level of color similarity between melanoma‐affected and ‐nonaffected areas. In this paper, we present a fully automated method for segmenting the skin melanoma at its earliest stage by employing a deep‐learning‐based approach, namely faster region‐based convolutional neural networks (RCNN) along with fuzzy k‐means clustering (FKM). Several clinical images are utilized to test the presented method so that it may help the dermatologist in diagnosing this life …