This Project aims to provide accurate plant disease predictions built over a DenseNet deep Learning Model with below configurations
input_2 (InputLayer) [(None, 64, 64, 3)] 0
conv2d (Conv2D) (None, 64, 64, 3) 84
densenet121 (Functional) (None, None, None, 1024 7037504
global_average_pooling2d ( (None, 1024) 0
GlobalAveragePooling2D)
batch_normalization (Batch (None, 1024) 4096
Normalization)
dropout (Dropout) (None, 1024) 0
dense (Dense) (None, 256) 262400
batch_normalization_1 (Bat (None, 256) 1024
chNormalization)
dropout_1 (Dropout) (None, 256) 0
... Total params: 7308963 (27.88 MB) Trainable params: 7222755 (27.55 MB) Non-trainable params: 86208 (336.75 KB)
