… In this work, the skin cancer was classified based on skin lesions confirmed by pathology. …
by using the transfer learning-based models to classify it either as malignant or benign cancer. …

… shown superior skin cancer detection than people (Nugroho et al., 2019). From this point of
view, in this study, it is aimed to classify skin cancer by transfer learning-based deep learning …

… Primary Objective: Our primary objective is to classify the skin cancers to their types by
building the best model using convolutional neural network and transfer learning. …

… limitations mentioned earlier and improve skin cancer diagnosis accuracy, image-based
Computer-aided Diagnosis (CAD) has been developed ([16]). The classification step in an SLC-…

… In this study, a threshold-based automatic approach for skin cancer detection, classification,
… The current study concentrates on skin cancer detection, classification, and segmentation. …

… study, deep learning models are developed for skin cancer … For the rest of the models,
transfer learning strategies are … and transfer learning methods on skin cancer classification …

… The resultant feature map from the DLCNN architecture is applied to the transfer learning
model for the classification of skin cancer. Thus, the test image is not matched with the anyone …

… Deep learning algorithms … field of skin cancer research, Esteva et al. [6] in 2017 demonstrated
the usage of a pre-trained Inception v3 CNN model to classify 129,450 clinical skin cancer …

… In the field of transfer learning and federated learning, there are several new … skin cancer.
In this section, state-of-the-art methods dependent on transfer learning and federated learning …

… cancers, on the other hand, can grow in elements of the skin … skin cancer lesion found across
globe. It is considered the most dangerous kind of skin cancer according to the Skin Cancer …