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README.md
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@@ -28,22 +28,22 @@ This project is a web application developed using Flask that allows users to upl
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### Models
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- **Potato Disease Classification Model**
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- **Classes:**
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Potato Early Blight
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Potato Late Blight
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Potato Healthy
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- **Techniques Used:**
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Convolutional layers for feature extraction.
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Batch normalization and max pooling for enhanced training stability and performance.
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Dropout layers to prevent overfitting.
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- **Tomato Disease Classification Model**
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- **Classes:**
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-
Tomato Early Blight
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-
Tomato Late Blight
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Tomato Healthy
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- **Techniques Used:**
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### Web Application
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### Models
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- **Potato Disease Classification Model**
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- **Classes:**
|
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+
Potato Early Blight,
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+
Potato Late Blight,
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Potato Healthy
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- **Techniques Used:**
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+
- Convolutional layers for feature extraction.
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+
- Batch normalization and max pooling for enhanced training stability and performance.
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+
- Dropout layers to prevent overfitting.
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- **Tomato Disease Classification Model**
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- **Classes:**
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+
Tomato Early Blight,
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Tomato Late Blight,
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Tomato Healthy
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- **Techniques Used:**
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- Similar architecture to the potato model with appropriate adjustments for tomato disease classification.
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- Batch normalization, max pooling, and dropout layers are also used here.
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### Web Application
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