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resnet50v2

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This research enhances early disease diagnosis by analyzing retinal blood vessels in fundus images using deep learning. It employs eight pre-trained CNN models and Explainable AI techniques.

  • Updated Apr 29, 2024
  • Jupyter Notebook

this project is based on brain tumor detection using image classification and deep learning models like CNN , KNN , Logistic Regression , XG-Boost , Random Forest and RESNET50V2. After testing these 6 models the best model among these 6 with high accuracy is taken and trained to the model and predicted the out put

  • Updated Oct 19, 2023
  • Jupyter Notebook

This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.

  • Updated Aug 29, 2024
  • Jupyter Notebook

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