When significant neurons of trained neural networks is dropped gradually, the trained model loses it ability to classify the label correctly.
When top neurons of trained neural network of a specific class is dropped gradually, the trained model loses it ability to classify the label correctly.
Interestingly, the model starts focusing on other regions of an Image with probability getting distributed among other classes.
Consider you have strong memories of particular events in your life like going to college or the time you met with an
accident and it is stored as neuron among billions of neurons in your brain and now you vaguely remember those events because your neurons have vanished
slowly as the years have passed.
Similarly now compare those with neurons of your model which has learnt to identify a scene but as i drop some of those neurons, it starts loses ability to
understand its role and vaguely predicts with available neurons. Interest Concepts, Don’t you think?
pip install -r requirements.txt
Top Most Neuron refers to neurons with large weight value and Bottom Most Neuron refers to weights with least value.