Category: Skin Cancer
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Convolution Neural Networks for Predicting Skin Lesions of Melanoma by Segmentation
Abstract Skin lesions are significant in determining dermatological medical conditions globally. Early diagnosis of malignant melanoma by dermoscopy imaging considerably will increase the survival rate. Throughout this paper, we tend to present deep learning-based approaches to resolve 2 issues in skin lesion analysis employing a dermoscopic image containing the tumor. Estimation of these biomarkers are…
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Skin Cancer: Convolutional Neural Network Based Skin Lesion
Analysis towards Melanoma Abstract Melanoma is only harmful in human epidemic diseases and the level of these diseases is increasing continuously. Computers are not more intelligent than humans, but it is easy to find some information easily, which may not be easily apparent to the human eye. Such as: skin color variations or taxa variations.…
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Extent Of Applying Artificial Intelligence In The Diagnosis Of Skin Cancer
Before delving into the content of this essay, it is crucial to understand why this argument is valid. Cancer is a fatal disease and the chances of survival, especially for skin cancer, vary greatly depending on how early and accurately it is diagnosed (The Skin Cancer Foundation, 2019). Recognising cancerous cells from benign ones requires…
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Melanoma Skin Cancer Detection Using Image Processing
Abstract Among the three basic types of skin cancer, viz, Basal Cell Carcinoma (BCC), Squamous Cell Carcinoma (SCC) and Melanoma, Melanoma is the most dangerous in which survival rate is very low. The proposed skin cancer detection technology is broadly divided into four basic cmponents, viz., image preprocessing which includes hair removal, de-noise, sharpening, resize…