Deep learning based medical image classifiers have shown remarkable prowess in various
application areas like ophthalmology, dermatology, pathology, and radiology. However, the …

Dermatologists often diagnose or rule out early melanoma by evaluating the follow-up
dermoscopic images of skin lesions. However, existing algorithms for early melanoma …

There are a lot of hidden dangers in the change of human skin conditions, such as the
sunburn caused by long-time exposure to ultraviolet radiation, which not only has aesthetic …

We propose an attention-based method for melanoma recognition. The attention modules,
which are learned together with other network parameters, estimate attention maps that …

Skin cancer is the most common of all cancers that exist in the world and melanoma is the
deadliest among all the skin cancers. It is found that melanoma roughly kills a person every …

Early detection of skin cancers like melanoma is crucial to ensure high chances of survival
for patients. Clinical application of Deep Learning (DL)-based Decision Support Systems …

With the rapid increase in the cases of deadly skin cancer, the classification on different
types of skin cancer has been emerging as one of the most significant issues in the field of …

Skin cancer is one of the deadliest types of all cancers and melanoma is the severest form of
it. In this paper, we have used three state-of-the-art deep convolutional neural network …

The influence of Artificial Intelligence (AI) on society is increasing, with applications in highly
sensitive and complicated areas. Examples include using Deep Convolutional Neural …

Skin cancer is one of the most common types of cancers in the world and is a big concern for
people's health. In recent years, automatic algorithms to recognize skin cancers from …