International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
www.irjet.net
Skin Cancer Detection Using Deep Learning Techniques Ragavendra S1, Subhash S2, Nishanth B3, Chandan J4 1 Assistant Professor, Department of Computer Science and Engineering, Jnanavikas Institute of Technology, Karnataka,India 2Undergraduate Student, Department of Computer Science and Engineering, Jnanavikas Institute of Technology, Karnataka, India 3Undergraduate Student, Department of Computer Science and Engineering, Jnanavikas Institute of Technology, Karnataka, India 4Undergraduate Student, Department of Computer Science and Engineering, Jnanavikas Institute of Technology, Karnataka, India -------------------------------------------------------------------***------------------------------------------------------------------------Abstract – Less people are aware of the symptoms of skin illness and how to prevent it, making it one of the deadliest forms of cancer. The aim of this study is to identify and categorize different forms of skin cancer using machine learning and image processing techniques. We produced a pre-processing image for this endeavor. We lowered the dataset's size, To fit the needs of each model, the photos were resized and had their hairs removed. The EfficientNet B0 skin ISIC dataset was trained using pre-trained ImageNet weights and modified convolution neural networks.
Keywords- Disease Detection, Image Processing ,YOLOR, EfficientNet B0, Quantification INTRODUCTION Skin cancer, which is on the rise globally, is the sixth most common cancer. Normally, tissues are made up of cells, and tissues make up the skin. Consequently, cancer is caused by abnormal or unregulated cell development in connected tissues or other nearby tissues. Numerous factors, such as UV radiation exposure, a weakened immune system, a family history of the disease, and others, may affect the development of cancer. These types of cell development patterns can appear in both benign and malignant tissues. Benign tumours, which are cancerous growths, are sometimes mistaken for minor moles. Malignant tumours,on the other hand, are treated like a cancer that may spreadfatally. The body's other tissues could also be harmed by them. Basal cells, squamous cells, and melanocytes are the three types of cells that make up the skin's outer layer. These are at fault for the tissues' development of cancer. The three fatal forms of skin disease (SCC) are melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Vascular lesions, actinic keratosis (AK), benign keratosis, dermatofibroma, and melanocytic nevus are a few examples of further types. Melanoma is the most dangerous type of cancer because it can come back even after treatment. The United States and Australia have the highest rates of skin cancer.
RELATED WORK The study by YaliNie& team, Automatic Melanoma Yolo Deep Convolution Neural Networks for Detection" [1] describes yolo approaches based on DCNNs that are used to identify melanoma. For melanoma detection in lightweight system
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