Lecture
3.12 Flexible Quality Inspection: Tackling the challenges of AI-based automation
- 14.11.2024 at 14:40 - 15:00
- Future Control Stage (C5.259)Artificial Intelligence & ML
- Language: English
- Type: Lecture
Lecture description
The challenges of implementing AI-based automation in quality inspection include insufficient data on defective samples and the low reliability of Deep Learning systems in dynamic environments. This talk will explore how flexible quality inspection can address these issues. We will introduce our FAST (Feedback-guided Automation of Sub-Tasks) approach, which facilitates partial automation and continuous improvement. Attendees will also learn about modular concept models and tools that empower experts to develop tailored AI solutions, enhancing the effectiveness of quality inspection processes.
Further lectures
- 10:00 - 10:203.1 Demystifying the Open Source Graphics Stack on Linux: From Kernel to User Space with a Focus on Embedded Systems
- 10:20 - 10:403.2 Building and maintaining embedded Linux distributions with Yocto and Mender
- 10:40 - 11:003.3 Embedded Linux: Armbian or Yocto?
- 11:00 - 11:203.4 Getting Up to Speed with RTOS-based Firmware Development
- 11:20 - 11:403.5 Managing compliance: Open Source license obligations checklists
- 11:40 - 12:003.6 Meeting the cybersecurity needs of embedded systems
- 12:20 - 12:403.8 Mesa3D Unveiled: From glDrawArrays(…) to GPU Magic
- 13:40 - 14:003.9 Enhancing interoperability and performance for low-power Wi-Fi 6/6E IoT devices
- 14:00 - 14:203.10 Embedded-AI in a nutshell - process, use cases and a look in to the future
- 14:20 - 14:403.11 How to use NVIDIA TAO Models that run on Orin to work on Embedded ARM based MCU