skin-cancer-classification

There are 0 repository under skin-cancer-classification topic.

• SCASTELLANO6044 / TFT-AI

  This project uses TensorFlow to implement a Convolutional Neural Network (CNN) for image classification. The goal is to classify skin lesion images into different categories. The dataset used is HAM10000, which contains skin lesion images with associated metadata. The actual accuracy of the model is 90%. 🚀🚀

  cnncnn-classificationdeep-learningham10000image-classificationskin-cancer-classificationskin-cancer-detection
  Language:Python 2

• syedissambukhari / skin-cancer-detection-using-ddi-dataset

  A Convolutional neural network (CNN)model to train and detect skin cancer (benign and malignant) disease using DDI(Diverse Dermatology Images)Dataset.

  cnn-classificationddiskin-cancer-classificationskin-cancer-detectionddi-dataset
  Language:Jupyter Notebook 2

• akashkriplani / melanoma-skin-cancer-detection

  Build a CNN based model which can accurately detect melanoma

  class-imbalance-problemcnn-classificationdata-augmentationkeras-tensorflowmelanoma-detectionskin-cancer-classification
  Language:Jupyter Notebook 1

• shahdhairya51 / skin-cancer-classification

  convolutional-neural-networksdeep-learningimage-classificationkagglekeras-tensorflowmachine-learningmedical-imagingskin-cancerskin-cancer-detectionskin-lesion-classificationskin-lesion-imageskin-cancer-classificationmedicalmedical-aihealthcare
  Language:Jupyter Notebook 1

• MatthewJansen / Application-of-CCT

  A comprehensive guide on how to implement and train a Compact Convolutional Transformer model that is specifically designed for classifying skin cancer.

  compact-convolutional-transformercomputer-visionimage-classificationneural-networkskin-cancer-classificationvision-transformer
  Language:Jupyter Notebook 0

• ablanco1950 / SkinLesionDetection_Resnet_Pytorch

  Detection of skin lesions (among 7 classes) using the file https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DBW86T and using the pytorch resnet model. The success rate for the specific test file (unseen data) that comes with the download file is 81.13%.

  pythonpytorchresnet-50skin-cancer-classificationskin-lesionsvidir
  Language:Python

• kunaltilaganji / Classification-of-Dermatoscopic-Images

  Skin Cancer Lesion Detection

  deep-neural-networksskin-cancer-classification
  Language:Jupyter Notebook