… has adopted the use of deep learning techniques. In this work, we performed … classification
of skin images using convolutional neural networks for the diagnosis of melanoma skin cancer…

… by the dermatologists in skin cancer classification [75]. The initial efforts using dermoscopy
images were restricted to the classification of benign and melanoma skin cancer lesions [61]. …

… cancer cells. The aim of this study was to try to classify images of skin lesions with the help of
convolutional … into two major categories: Melanoma (Malignant) and non-melanoma (Benign…

… uptick in people diagnosed with nonmelanoma and melanoma skin cancers, respectively.
Melanoma can be identified in that only one in three cases of cancer, as stated by the World …

… An automated model for skin cancer classification has … using the theory of transfer
learning for the Alexnet and Resnet50 architecture to classify tumors as melanoma or not-melanoma. …

… The incidence of skin cancers has been increasing over the past decades at an alarming …
3 million non-melanoma skin diseases and 132,000 melanoma skin malignant growths happen …

… identify skin cancer and benign tumor lesions automatically using the Convolutional Neural
Network (… Non-melanoma skin cancers, such as basal cell carcinoma and squamous cell …

… of skin cancers, such as melanoma and focal cell carcinoma. The recognition and the
classification of skin malignant … The deep learning architectures such as recurrent networks and …

… have integrated image augmentation, deep convolutional neural network (DCNN), and …
classification demonstrate that the proposed approach can successfully distinguish skin cancer …

… in the accuracy of skin cancer classification using convolutional neural networks (CNNs). …
[7-9] dermatologists in challenging binary melanoma detection and multiclass skin cancer …