{"id":1474,"date":"2020-07-10T19:54:59","date_gmt":"2020-07-10T17:54:59","guid":{"rendered":"https:\/\/serengeti.pepwebdigital.hr\/?p=1474"},"modified":"2021-01-02T17:46:19","modified_gmt":"2021-01-02T16:46:19","slug":"tire-recognition-meets-machine-learning-v2-step-by-step-approach-franks-case-part-2","status":"publish","type":"post","link":"https:\/\/serengetitech.com\/de\/business\/tire-recognition-meets-machine-learning-v2-step-by-step-approach-franks-case-part-2\/","title":{"rendered":"Tire Recognition meets Machine learning v.2: Step by step approach \u2013 Frank\u2019s case [PART 2]"},"content":{"rendered":"

While in first part about Frank\u2019s case we explained what the problem was, modus operandi and taken steps, here we are going to describe approach conducted and what was the final output and business benefits.<\/p>\n\n\n\n

Taken approach - step by step  <\/strong><\/h2>\n\n\n\n

1. PoC \u2013 choose the scope<\/strong><\/h3>\n\n\n\n

Building trust with a client and demonstrating the solution is usually achieved through Pilot\/PoC stage. Choosing a scope as a small percentage of total unique tire number which need to be identified is a good starting point. All the necessary components of the system will be present within the Pilot, but the data acquisition\/annotation phase will be much shorter and RoI might be easily calculated after it.<\/p>\n\n\n\n

2. Monitoring the data acquisition and labeling the data<\/strong><\/h3>\n\n\n\n

During the data acquisition phase ardent monitoring should be performed either to detect some algorithmic flaws, system setup flaws or careless behavior by the people putting the tires on the conveyor belt. Allowing the errors to continue will in all cases prolong the Pilot phase, which is not in anyone\u2019s interest, but most importantly it will erode the trust with the client. Make sure you have very high level of confidence in your software and procedures before pointing fingers at employees.<\/p>\n\n\n\n

Labeling the data should be performed in parallel with the data acquisition phase and is supported by custom app developed to speed up the process as much as possible using suggestions from machine learning models.<\/p>\n\n\n\n

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