• Isha Mulajkar
• Mr. R.L. Nandargi
• Vasanti Mule
• Bhatesh Patil

Skin cancer is one of the major types of cancers with an in-creasing incidence over the past decades. Accurately diagnosing skin lesions to discriminate between benign and malignant skin lesions is crucial to ensure appropriate patient treatment. While there are many computerised methods for skin lesion classification, convolutional neural networks (CNNs) have been shown to be superior over classical methods. In this work, we propose a fully automatic computerised method for skin lesion classification which employs optimised deep features from a number of well-established CNNs and from different abstraction levels. It trains the model and gives the accuracy of 96%. The proposed work helps early identification of skin disease and can be validated and treated appropriately by medical practitioners.

Skin Lesion Classification using Deep Learning

"Skin Lesion Classification using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.564-566, May-2023, Available :http://www.jetir.org/papers/JETIRFX06098.pdf

"Skin Lesion Classification using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp564-566, May-2023, Available at : http://www.jetir.org/papers/JETIRFX06098.pdf