How to teach an AI vision system to check quality requirements

Today, quality requirements can be transferred to AI-based machine vision systems through machine learning in order to ensure product quality in automated production processes. In this way, manual visual inspections are reduced and, at the same time, defects caused by scratches, cracks and shape defects become visible and can be avoided at an early stage. This allows defective products to be reliably sorted out before they go to further processing or directly to the customer.

In this Vision Channel session, we will show you possible use cases and also how the technology remains controllable through the cloud-based AI Vision Studio IDS NXT lighthouse. And you will see that the intuitively designed user interface can be handled by anyone, even without in-depth knowledge in application programming or dealing with AI.

- IDS NXT Website: [ Ссылка ]
- Start right now with IDS NXT ocean Creative Kit: [ Ссылка ]
TECHNICAL ARTICLES:
- It´s time for AI: [ Ссылка ]
- AI - playground or industrial tool?: [ Ссылка ]
- AI for the food industry: [ Ссылка ]
IDS Vision Channel:
- Build AI vision apps without coding: [ Ссылка ]
- Intelligent sorting for higher muesli quality: [ Ссылка ]
- More about AI: [ Ссылка ]

00:25 Session description
02:38 Introduction in AI vision
05:44 Application - Check fit of snap rings
09:24 Application - Wood check
11:35 AI vision with linescan
13:44 AI based system monitoring
15:44 Application - Identify bottle tops
16:49 Application - Smart Farming
18:23 Easy AI Vision workflow for everyone
23:39 CTA - How to evaluate AI vision without camera

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