Improving Accuracy of the Deep Learning Model
You can try bunch of things like:


Data augmentation. 
Transfer learning on model trained on similar dataset.
Train multiple neural network with different intialisation of weights and then take majority voting during inference.


The last point matters if you're training from scratch because weights intialisation direct the model towards different minima. So with average of different networks you're essentially taking average of different minimas which might increase overall accuracy.