基于卷积神经网络的打印错误检测
Print Error Detection using Convolutional Neural Networks
摘要：
本文讨论了印刷错误自动检测系统的需求和卷积神经网络在这种应用中的有效性。我们认识到需要一个包含打印错误样本的数据集，并提出了一种方法来人工生成一个。我们讨论的算法来产生这样的数据，以及这种approach的局限性和优点。我们最终训练的网络在测试中给出了99.83%的准确率。我们进一步评估如何实现这种效率，以及可以测试哪些修改以进一步提高结果。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
