… skin cancer detection in recent years. In this paper, we thoroughly discuss and analyze skin
cancer detection techniques based on deep learning. … approaches of deep learning, such as …

… The classification accuracy using deep learning was 92.89%. In this paper, a deep convolutional
neural network (DCNN) is applied to classify the color images of skin cancer into three …

… Convolutional Neural Network (CNN) or ConvNet, are a class of deep neural networks, … to
develop a skin cancer detection CNN model which can classify the skin cancer types and help …

… Therefore, skin cancer screening is necessary. One of the best methods to accurately and
swiftly identify skin cancer is using deep learning (DL). In this research, the deep learning …

… used in skin cancer … skin cancer classification are still scarce. Therefore, in this article, we
provide a comprehensive overview of the latest deep learning-based algorithms for skin cancer …

… a classification system by deep learning for brown to black pigmented skin lesions, as the …
The skin tumor classification system using deep learning showed better results in both six- …

… skin cancer type, and methods implemented, and the success rate. Even though Deep learning
using … We will discuss, how Deep learning using CNN helped us and its vulnerabilities. …

… In this study, we show that two different deep learning methods can be used to diagnose
skin cancer with high accuracy rates. The results obtained by using these two algorithms are …

… Skin cancer is a major public health problem around the world. Its early detection is very …
In this context, over the past few years, deep learning models applied to automated skin cancer …

… years, deep learning models applied to computerized skin cancer … a deep learning network
has been selected and trained by the author for the analysis of more than 24,000 skin cancer …