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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
42
- Tomato Late Blight
43
  Tomato Healthy
44
  - **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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  ### Models
29
  - **Potato Disease Classification Model**
30
  - **Classes:**
31
+ Potato Early Blight,
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+ Potato Late Blight,
33
  Potato Healthy
34
  - **Techniques Used:**
35
+ - Convolutional layers for feature extraction.
36
+ - Batch normalization and max pooling for enhanced training stability and performance.
37
+ - Dropout layers to prevent overfitting.
38
 
39
  - **Tomato Disease Classification Model**
40
  - **Classes:**
41
+ Tomato Early Blight,
42
+ Tomato Late Blight,
43
  Tomato Healthy
44
  - **Techniques Used:**
45
+ - Similar architecture to the potato model with appropriate adjustments for tomato disease classification.
46
+ - Batch normalization, max pooling, and dropout layers are also used here.
47
 
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  ### Web Application