Print Error Detection using Convolutional Neural Networks
  This paper discusses the need of an automated system for detecting print
errors and the efficacy of Convolutional Neural Networks in such an
application. We recognise the need of a dataset containing print error samples
and propose a way to generate one artificially. We discuss the algorithms to
generate such data along with the limitaions and advantages of such an
apporach. Our final trained network gives a remarkable accuracy of 99.83\% in
testing. We further evaluate how such efficiency was achieved and what
modifications can be tested to further the results.
