AI versus rule-based image processing: expert panel on the future of vision systems
This video explores the critical differences between rule-based image processing and AI-driven vision systems in industrial applications. Our panel of experts from VMT, IDS, Fraunhofer IAO, and Trumpf discuss when AI makes sense, where rule-based models still excel, and how hybrid approaches are shaping the future.
Learn why data quality, retraining, and explainability are critical for successful AI (Artificial Intelligence) deployment. Our experts share practical insights on hybrid approaches, regulatory considerations, and how AI can support development and maintenance tasks. If you want to understand where machine vision is heading, this video is essential viewing.
Topics covered
- When AI vision outperforms rule-based models
- Why rule-based systems remain relevant in stable conditions
- The importance of data quality and retraining for AI success
- Explainable AI and regulatory compliance in industrial settings
- Future trends: hybrid systems and vision-language models
- Why expert knowledge is still crucial for AI implementation
Video timeline
- 00:00 - When do rule-based models make sense or still make sense?
- 04:40 - What about retraining data?
- 07:46 - What to keep in mind when working with AI (black box)?
- 11:56 - Vision language models
- 14:36 - Can anyone work with AI? Is AI simple?
- 16:59 - Q&A
Who should watch
This video is ideal for machine vision engineers, AI developers, system integrators, and decision-makers in manufacturing who want to understand the practical and strategic aspects of AI vision versus rule-based image processing.
Watch now to gain expert insights into the future of industrial image processing.
