https://github.com/samir-atra/cancerdetector

The final project of AI50xIraq course is found in the commit on 21-3-2023
https://github.com/samir-atra/cancerdetector

cancer-detection cnn dataset inceptionv3 matplotlib numpy opencv tensorboard tensorflow tensorflow-tutorials transfer-learning

Last synced: 19 days ago
JSON representation

The final project of AI50xIraq course is found in the commit on 21-3-2023

• Host: GitHub
• URL: https://github.com/samir-atra/cancerdetector
• Owner: Samir-atra
• License: cc0-1.0
• Created: 2022-06-11T09:30:13.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-27T19:24:57.000Z (about 1 year ago)
• Last Synced: 2024-12-21T06:13:13.978Z (19 days ago)
• Topics: cancer-detection, cnn, dataset, inceptionv3, matplotlib, numpy, opencv, tensorboard, tensorflow, tensorflow-tutorials, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 608 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# CancerDetector

The final project of AI50xIraq course. can be found in the commit on 21-3-2023, and after that date the project has been updated beyond the course scope. 

below is the description for the course project:

trained on the dataset in the link: https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri

The "Meningioma_Detector" version of the project is fitted on part of the dataset mentioned above, to detect positive and negative meningioma tumor cases and it works with 93% accuracy, and the "Cancer_Detector" version is built to detect positive and negative cases of (Glioma, Meningioma, pituitary) brain tumor and it works with 95% accuracy, and it's fitted on both the datasets above and the following: 

https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset?resource=download&select=Training

model file for transfer learning version could be found at: https://drive.google.com/drive/folders/1o7ts623pJQxxuOs5kQBkyjEyorH8lT0X?usp=sharing