How can we create neural net to detect false predictions?
One thing you could try is to change the softmax activation on your final layer to sigmoid. This will give a value between zero and one for each class, the sum of which may not equal one. This means that for a given example there may be more than one output neuron activated, or no output neurons activated, in which case you can treat the example as 'unsure' and manually check it out. In the case that there is exactly one output neuron activated (should be most of the time), that should be the classification given.