Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …

Skin cancer is one the most dangerous types of cancer and is one of the primary causes of
death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early …

Skin cancer is one of the top three perilous types of cancer caused by damaged DNA that
can cause death. This damaged DNA begins cells to grow uncontrollably and nowadays it is …

Computer-aided skin cancer classification systems built with deep neural networks usually
yield predictions based only on images of skin lesions. Despite presenting promising results …

Skin cancer (SC) is one of the most prevalent cancers worldwide. Clinical evaluation of skin
lesions is necessary to assess the characteristics of the disease; however, it is limited by …

Skin cancers, such as melanoma, can be difficult to spot in their early stages because they
often resemble benign moles. Early detection of melanoma is crucial as it increases 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 …

Due to the successful application of machine learning techniques in several fields,
automated diagnosis system in healthcare has been increasing at a high rate. The aim of the …

Computer-aided skin cancer detection systems built with deep neural networks yield
overconfident predictions on out-of-distribution examples. Motivated by the importance of out …

Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for
the recognition of multiclass pigmented skin lesions (PSLs). At an early stage, the manual …