DSCC_Net: Multi-Classification Deep Learning Models for Diagnosing of Skin Cancer Using Dermoscopic Images
National College of Business Administration and Economics · University of Management and Technology · +2 more institutions
Abstract
Skin cancer is one of the most lethal kinds of human illness. In the present state of the health care system, skin cancer identification is a time-consuming procedure and if it is not diagnosed initially then it can be threatening to human life. To attain a high prospect of complete recovery, early detection of skin cancer is crucial. In the last several years, the application of deep learning (DL) algorithms for the detection of skin cancer has grown in popularity. Based on a DL model, this work intended to build a multi-classification technique for diagnosing skin cancers such as melanoma (MEL), basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanocytic nevi (MN). In this paper, we have…
Citation impact
- FWCI
- 44.51
- Percentile
- 100%
- References
- 78
Authors
6- MTMaryam Tahir
National College of Business Administration and Economics
- ANAhmad Naeem
University of Management and Technology
- HMHassaan Malik
National College of Business Administration and Economics, University of Management and Technology
- JTJawad Tanveer
Sejong University
- RARizwan Ali NaqviCorresponding
Sejong University
Topics & keywords
- Skin cancer
- Deep learning
- Artificial intelligence
- Convolutional neural network
- Benchmark (surveying)
- Cancer
- Basal cell carcinoma
- Melanoma
- Good health and well-being