Very slow convergence with CNN I am new to deep learning. I am working on training an SSD model on a set of small objects. I am using Adam gradient descent for optimization and a large input (800x800), but I seem to only get an improvement of 0.010 after every 20 or so epochs(350 steps). 

What can I do or look for to speed up convergence on this model?
Implement the below mentioned techniques and check


Add Batch Normalization
Increase the learning rate
Standard/Normalize the inputs if you have not done it already