Skin Cancer Identification and Classification
| dc.contributor.author | G PAVAN KUMAR: 1NH20CS279 V PUNEETH KUMAR: 1NH20CS292 ABHISHEK CRM: 1NH20CS298 | |
| dc.date.accessioned | 2025-06-30T08:49:51Z | |
| dc.date.available | 2025-06-30T08:49:51Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The largest organ of our human body is skin and skin cancer is most predominating type of cancer that influences millions of people per annum. Survival rate of patients decreases steeply if cancer is not detected in early stages. However, early detection of cancer is a very strenuous and costly process. The skin cancer dataset consists of benign and malignant skin cancer dataset. According to researchers in earlier stages it is hard to detect due to minute difference compared to normal skin lesions. Therefore, identification of cancerous skin lesion in early stages is a difficult matter. In this review we are going to discuss various technologies that can be used for skin cancer detection and classification and their results. The common approach for early detection of skin lesion is divided into four steps they are as follows: pre- processing, segmentation, feature extraction, and classification. The deep learning algorithm is used to identify the skin cancer disease. It will help to easily identify earlier stage of skin cancer | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/19532 | |
| dc.language.iso | en | |
| dc.publisher | New Horizon College of Engineering | |
| dc.title | Skin Cancer Identification and Classification | |
| dc.type | Learning Object |