Paper Title
Unveiling Dermatological Threats: Deep Learning-Based Skin Cancer Classification from Lesion Images
Article Identifiers
Authors
Dr.P.Manikandaprabhu , Mr.V.Pradish
Keywords
Benign lesions, Convolutional neural network (CNN), Deep learning, DenseNet, ISIC archive, Malignant lesions, VGG16
Abstract
In the present-day period, pores and skin disorders have emerged as major health issues, necessitating advanced analysis techniques. Partitioning the lesion vicinity is a vital step in deep learning-based computer-aided analysis, which has become famous as a beneficial device to help doctors in diagnosing patients. However, good-sized pixel-level labeling is generally wanted for completely supervised training with conventional scientific image segmentation techniques, that is a hard and specialized understanding-extensive manner. This novel approach to pores and skin lesion area segmentation that simplest makes use of photo-stage labels to solve those issues and reduces the costs of pixel-stage labeling. The purpose of this study is to research and determine strategies designed specifically for the identity of pores and skin melanoma. The goal is to evaluate the efficacy and relevance of those various strategies in improving the sector of cancer detection and prognosis. In cutting-edge times, skin illnesses pose sizable fitness concerns, driving the need for advanced diagnostic equipment. This novel method is proposed that utilizes photo-stage labels to segment skin lesion regions, decreasing the want for extensive pixel-stage labeling. The study focuses on evaluating approaches customized for the detection of skin melanoma, including traditional dermatoscopic image analysis and overall body assessments. Through an exploration of these methods, the aim is to assess their effectiveness in enhancing melanoma detection and diagnosis.
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How To Cite (APA)
Dr.P.Manikandaprabhu & Mr.V.Pradish (March-2024). Unveiling Dermatological Threats: Deep Learning-Based Skin Cancer Classification from Lesion Images. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), g287-g292. https://ijnrd.org/papers/IJNRD2403634.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : g287-g292
Other Publication Details
Paper Reg. ID: IJNRD_216524
Published Paper Id: IJNRD2403634
Downloads: 000121986
Research Area: Computer Science & TechnologyÂ
Country: Coimbatore, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403634.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403634
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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