Join us to learn how to develop and deploy AI-driven visual inspection systems using MATLAB.
This webinar covers end-to-end workflows, including cases where abnormal data is limited, real-time deployment to hardware.
End-to-end development workflow for visual inspection.
Real-time deployment demo using Single Board Computer + PLC.
Introduction to MATLAB's Automated Visual Inspection Library.
Low-code tools and GUI apps for human-in-the-loop workflows.
Customer use cases (Kansai Electric, Dexerials, Mitsui Chemicals, Yachiyo Engineering).
Build AI models without needing defect data (unsupervised learning).
Deploy to edge devices, GPUs, Raspberry Pi, PLC, and more.
Generate optimized C/C++ code using MATLAB Coder.
Package solutions as executable or web-based apps.
Reduce time from R&D to production with integrated workflows.
Visual inspection and QA engineers.
Automation and control system engineers.
Data scientists focused on industrial AI.
Technical managers driving internal digital transformation.
Gerald Reymari Cagayan
Application Engineer
Gerald specializes in AI, data science, and electro-optical engineering. With over five years of experience supporting industries across Southeast Asia, he helps teams accelerate AI adoption in quality control and automation. With over five years of data science experience supporting industries across Southeast Asia, he helps teams accelerate by adopting AI and data science techniques to further improve data gathering and analysis.
He holds a Master’s degree in Engineering from Taiwan, where he developed a nano-level detection system using lab-on-a-chip technology. With a strong background in both research and industry application, Gerald brings a practical, solution-focused approach to integrating AI with real-world systems.
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