Topic: skin-cancer-classification Goto Github
Some thing interesting about skin-cancer-classification
Some thing interesting about skin-cancer-classification
skin-cancer-classification,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%.
User: ablanco1950
skin-cancer-classification,Build a CNN based model which can accurately detect melanoma
User: akashkriplani
skin-cancer-classification,This repository contains the implementation and supplementary materials for the paper titled "Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks."
User: echelon2718
Home Page: https://arxiv.org/abs/2206.00272
skin-cancer-classification,Skin Cancer Lesion Detection
User: kunaltilaganji
skin-cancer-classification,A comprehensive guide on how to implement and train a Compact Convolutional Transformer model that is specifically designed for classifying skin cancer.
User: matthewjansen
Home Page: https://www.kaggle.com/code/matthewjansen/application-of-compact-convolutional-transformers/notebook
skin-cancer-classification,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%. 🚀🚀
User: scastellano6044
skin-cancer-classification,
User: shahdhairya51
Home Page: https://skinvision-ai.onrender.com/
skin-cancer-classification,A Convolutional neural network (CNN)model to train and detect skin cancer (benign and malignant) disease using DDI(Diverse Dermatology Images)Dataset.
User: syedissambukhari
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