https://github.com/ansh2709/dl-potato-disease-classification
Useful to predict the disease in potato leaves thus can predict disease like early blight and late blight used CNN,tensorflow etc
https://github.com/ansh2709/dl-potato-disease-classification
accuracy-score cnn-architecture computer-vision cross-validation f1-score keras-tensorflow resnet9 sparse-categorical-cross-entropy supervised-learning
Last synced: 7 months ago
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Useful to predict the disease in potato leaves thus can predict disease like early blight and late blight used CNN,tensorflow etc
- Host: GitHub
- URL: https://github.com/ansh2709/dl-potato-disease-classification
- Owner: Ansh2709
- Created: 2025-01-11T13:35:51.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-11T13:44:50.000Z (9 months ago)
- Last Synced: 2025-02-01T14:33:26.397Z (9 months ago)
- Topics: accuracy-score, cnn-architecture, computer-vision, cross-validation, f1-score, keras-tensorflow, resnet9, sparse-categorical-cross-entropy, supervised-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 3.15 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Used CNN deep learning technologies
Made Sequential->Convolution->Avg pooling->Flatten layers for the classification that is based on resnet9 architecture
Evaluated it using sparse categorical loss function for back propagation,used accurcay,f-1 score and confusion matrix for evaluation
Used matplotlib a python library to compare the accuracy and loss output for the train and test set