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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | XCEPTIONNET BASED SKIN CANCER DETECTION USING CONVOLUTIONAL NEURAL NETWORKS |
| Authors Name: | Shrikant Narayan Gagare , Mininath Bendre |
| Unique Id: | IJSDR2404172 |
| Published In: | Volume 9 Issue 4, April-2024 |
| Abstract: | Abstract: A significant improvement in prognosis and survival rates can be achieved by early detection of skin cancer, which is one of the most prevalent types of cancer worldwide. Convolutional neural networks (CNNs) have emerged as powerful tools for the automated analysis of medical images with advances in artificial intelligence and deep learning. We present a comprehensive review of the state-of-the-art methods used by CNNs for the detection of skin cancer in this paper. There are many challenges associated with skin cancer diagnosis, including the need to identify malignant lesions as soon as possible, in order to avoid unnecessary hospitalization. We then delve into the architecture and workings of CNNs, which illustrate their suitability for analyzing medical images. In addition, we explore a variety of datasets that are commonly used to train and test CNN models for detection of skin cancer. The purpose of this article is to provide a detailed description of pre-processing techniques, data augmentation strategies, and model architectures used in existing studies in order to improve the accuracy of the results. Moreover, we also discuss the evaluation metrics we use to determine the performance of CNN models, including sensitivity, specificity, accuracy, and AUC-ROC. The article concludes with an overview of future research directions and potential areas for improvement in the field of CNN-based skin cancer detection systems. |
| Keywords: | Keywords: Skin cancer detection, Convolutional Neural Networks, Deep Learning, Medical image analysis, Artificial Intelligence. |
| Cite Article: | "XCEPTIONNET BASED SKIN CANCER DETECTION USING CONVOLUTIONAL NEURAL NETWORKS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1188 - 1195, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404172.pdf |
| Downloads: | 000338175 |
| Publication Details: | Published Paper ID: IJSDR2404172 Registration ID:210735 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: 1188 - 1195 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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