Skin Cancer Detection Using Convolutional Neural Network

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@article{1703379,
      author = {Vardhaman Pravin Munot, Vishal Gugale, Deepak Singh},
      title = {Skin Cancer Detection Using Convolutional Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {5},
      number = {10},
      pages = {176-182},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703379.pdf},
      abstract = {Skin cancer is a deadly disease in humans. The need to diagnose skin cancer early has increased due to the rapid growth rate of melanoma skin cancer, high treatment costs, and mortality rates. These cancer cells are detected by hand and take time to heal in most cases. This paper has proposed a practical skin cancer screening program using image processing and machine learning. The characteristics of the affected skin cells are removed after the separation of dermoscopic images using the feature removal method. An in-depth approach based on learning convolutional neural network classifier is used for classification of extracellular features. 89.5% accuracy and 93.7% training accuracy were achieved after using a publicly available data set.},
      keywords = {Machine Learning; Convolution Neural Network; Information Search and Retrieval; Melanoma; Feature Extraction},
      month = {April},
  }