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https://github.com/jkanishkha0305/an-end-to-end-hybrid-learning-model-for-detection-of-covid-19-from-chest-xray-images
An end-to-end Hybrid Learning Model built using CNN+LSTM layers to detect covid-19 from Chest X-ray images. Comparative study has been performed along with modified CNN architectures of transfer learning models : Xception, MobileNet and VGG19. An end-trend web based application was developed using flask framework and was hosted using Heroku.
https://github.com/jkanishkha0305/an-end-to-end-hybrid-learning-model-for-detection-of-covid-19-from-chest-xray-images
deep-learning end-to-end hybrid-model transfer-learning
Last synced: 4 days ago
JSON representation
An end-to-end Hybrid Learning Model built using CNN+LSTM layers to detect covid-19 from Chest X-ray images. Comparative study has been performed along with modified CNN architectures of transfer learning models : Xception, MobileNet and VGG19. An end-trend web based application was developed using flask framework and was hosted using Heroku.
- Host: GitHub
- URL: https://github.com/jkanishkha0305/an-end-to-end-hybrid-learning-model-for-detection-of-covid-19-from-chest-xray-images
- Owner: Jkanishkha0305
- Created: 2022-07-04T13:02:55.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-04-29T11:13:30.000Z (over 1 year ago)
- Last Synced: 2023-08-30T01:17:16.553Z (about 1 year ago)
- Topics: deep-learning, end-to-end, hybrid-model, transfer-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 583 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0