Convolutional Neural Network :
Convolutional Neural Network(CNN) are trainable multistage
architecture. CNN implements the three architectural ideas to
ensure some degree of shift , scale, and distortion invarience, when
fully connected networks are used.
1 Local receptive fields : by this it takes into consideration topology of input to
calculate features.
2 Shared Weights : by this it can learn feature using less number of trainable
parameters compared to fully connected neural networks.
3 Spatial or Temporal Subsampling : to achive shifts and distortion invariance.
Convolutional Neural Network(CNN) are trainable multistage
architecture. CNN implements the three architectural ideas to
ensure some degree of shift , scale, and distortion invarience, when
fully connected networks are used.
1 Local receptive fields : by this it takes into consideration topology of input to
calculate features.
2 Shared Weights : by this it can learn feature using less number of trainable
parameters compared to fully connected neural networks.
3 Spatial or Temporal Subsampling : to achive shifts and distortion invariance.
