Multi-Class Skin Cancer Classification Using Vision Transformer Networks and Convolutional Neural Network-Based Pre-Trained Models

• Published in: Information (Basel) Vol. 14; no. 7; p. 415
• Main Authors: Arshed, Muhammad Asad, Mumtaz, Shahzad, Ibrahim, Muhammad, Ahmed, Saeed, Tahir, Muhammad, Shafi, Muhammad
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2023
• Subjects: Accuracy; Algorithms; Analysis; Artificial neural networks; Cancer; Classification; Color imagery; Datasets; Deep learning; Diagnosis; Disease; fine tuning; Health care industry; Lesions; Machine learning; Medical research; Melanoma; multi-class; Neural networks; Ozone; Performance evaluation; pretrained models; Skin cancer; skin cancer diagnosis; transfer learning; vision transformer; United States > US

Skin cancer, particularly melanoma, has been recognized as one of the most lethal forms of cancer. Detecting and diagnosing skin lesions accurately can be challenging due to the striking similarities between the various types of skin lesions, such as melanoma and nevi, especially when examining the...