Print Error Detection using Convolutional Neural Networks

• URL: http://arxiv.org/abs/2104.05046v1
• Date: Sun, 11 Apr 2021 16:30:17 GMT
• Title: Print Error Detection using Convolutional Neural Networks
• Authors: Suyash Shandilya
• Abstract summary: We propose a way to generate a print error sample artificially. Our final trained network gives a remarkable accuracy of 99.83% in testing.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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