inception model

1. InceptionV3

2. 2/28/2024 2
• Re-arrange images in dataset.
• Evaluate the new one on InceptionV3 model
InceptionV3
Optimizer: Adam
Weights: Imagenet
Batch size: 64
Image size input: 300 x 300
Trainable: 120 first layers / 316 layers
GlobalAveragePooling2D()
BatchNormalization()
Dropout(0.5)
Dense(1024, activation="relu")
Dense(512, activation="relu")
BatchNormalization()
Dropout(0.5)
Dense(4, activation="softmax")

3. 2/28/2024 3
With raw data

4. 2/28/2024 4
With preprocessd raw data

5. F-1Score ValAcc
BrownSpot 0.0857
Hispa 0.0530
LeafBlast 0.3846
Healthy 0.9023
Total 0.3329 0.5111
2/28/2024 5

6. 2/28/2024 6
With data after manually filtering

7. F-1Score ValAcc
BrownSpot 0.2890
Hispa 0.6007
LeafBlast 0.4451
Healthy 0.4909
Total 0.5081
2/28/2024 7

8. 2/28/2024 8
With preprocessd data after manually filtering

9. F-1Score ValAcc
BrownSpot 0.4636
Healthy 0.8046
Hispa 0.5323
LeafBlast 0.6387
Total 0.5843 0.5921
2/28/2024 9