Convolution neural network

This is a tensorflow (v12) implentation of deep layer convolution neural network on ORL faces recognition.

There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement).

#Runing the script

Unzip the dataset first

$ python convnet.py

Network parameters:

Layer 1:

• Filter size = 5
• Number of filters = 16
• max pooling = 2

Layer 2:

• filter size = 5
• number of filters = 36
• max pooling - 2

Regularisation: dropout (prob = 0.5)

A successful run will should display a plot of the loss function and accuracy as shown below..

#Visualisation of trained convolution filters

Layer 1 filters:

Layer 2 filters: