عرض سجل المادة البسيط

dc.contributor.author الهلة, كريمة
dc.contributor.author زيدان, شريفة
dc.date.accessioned 2023-10-11T09:52:16Z
dc.date.available 2023-10-11T09:52:16Z
dc.date.issued 2023
dc.identifier.uri https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/6532
dc.description.abstract Recently, Artificial Intelligence (AI) has permeated all areas of scientific study due to the solutions it provides in the field of health. The most common type of cancer in the world is skin cancer. Because early recognition is crucial for improving patient outcomes, we focused our efforts on developing a skin image classification model that differentiates benign from malignant melanoma. Based on a set of data generated using the CNN model, our model is based. To train our models, we used publicly accessible sites such as Google Colab and Kaggle. In this study, we applied the CNN architecture to a variety of information containing both benign and malignant data. In this project we have achieved a high accuracy in recognizing and classifying skin cancer with a score of 91%. EN_en
dc.publisher université Ghardaia EN_en
dc.subject artificial intelligence, 3D Configurable Model, Fuzzy Logic,CNN, Machine Learning, Deep Learning, Artificial Vision, and health care. EN_en
dc.title Detection and classification of skin cancer using CNN EN_en
dc.type Thesis EN_en


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