深度学习和人工智能可以用估计置信度解决测量问题

Uğurcan Akyüz
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摘要

过去,像许多公司一样,我们尝试使用光学字符识别(OCR)技术自动化手持式仪表等设备的数据采集,只学习OCR技术有其局限性;我们发现任何位置、光线、角度甚至眩光的变化都会影响OCR,导致糟糕的数字。所以我们改变了方向,转向了使用深度学习算法的人工智能(AI)。我们的目标是实现一种“边学边玩”的人工智能辅助解决方案,它将学习手持式仪表的阅读能力与人类一样好,甚至比人类更好。持续的学习/训练将训练AI在大多数照明条件下以任何角度读取测量值。经过训练的人工智能甚至可以聪明到理解基于前缀的缩放值。随着时间的推移,拥有更大的数据集,人工智能将能够读取几乎任何新的显示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning & Artificial Intelligence can Solve Measurement Problems with Estimated Confidence 
In the past, like many companies, we tried to automate the data collection of handheld meters and other devices using Optical Character Recognition (OCR) technology, only to learn OCR technology has its limitations; we discovered any change in position, lighting, angle and even glare would throw off the OCR, resulting in bad numbers. So we changed direction and switched to Artificial Intelligence (AI) with Deep Learning algorithms. Our goal was to implement a “learn as you go,” AI-assisted solution that will learn to read a handheld meter as good, or better than, a human. The continual learning/training would train the AI to read measurements at any angle, in most lighting conditions. The trained AI would even be smart enough to understand scaled values based on the prefixes. Over time, with a much larger data set, the AI would be able to read just about any new display.
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