Python 3.5.x
PIL
Pandas
Numpy
zipfile
matplotlib
TensorFlow
sklearn
Input Layer: It represent input image data. It will reshape image into single diminsion array. Example your image is 64x64 = 4096, it will convert to (4096,1) array.
Conv Layer: This layer will extract features from image.
Pooling Layer: This layerreduce the spatial volume of input image after convolution.
Fully Connected Layer: It connect the network from a layer to another layer.
Output Layer: It is the predicted values layer.
I have applied two different Transfer Learning approaches;
- Feature Extractor
- Fine Tunning