Author(s) :

Sukanya S. T

Conference Name :

International Conference on scientific innovations in Science, Technology, and Management (NGCESl-2023)

Abstract :

Skin cancer is a serious type of disease, malignant growth in particular, Basal Cell Carcinoma
(BCC), Squamous Cell Carcinoma (SCC) and Melanoma, Melanoma is the riskiest in which
endurance rate is extremely low. Melanoma can be detected earlier, potentially increasing
survival rates. The skin malignant growth location innovation is comprehensively partitioned
into four essential parts, viz., picture pre-processing which incorporates hair expulsion, declamor, honing, resize of the given skin picture, division which is utilized for portioning out the district of interest from the given picture. Segmentation can be done in a variety of ways.
K-means, threshold in histogram, and other segmentation algorithms are some common ones.
Features extraction from the segmented image and image classification using the segmented
image’s features set for this purpose, a variety of classification algorithms can be utilized.
Classification is performed by machine learning and deep learning algorithms in the most
recent skin cancer detection technology. Support vector machine (SVM), feed forward artificial
neural network, and deep convolutional neural network are the classification algorithms that
are utilized the most frequently. This paper gives an alternate kinds of improvement
calculations for skin malignant growth cell identification.

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