AI-Driven Visual Inspection for Semiconductor Manufacturing
Overview
As semiconductor manufacturing pushes the limits of scale and precision, visual inspection plays an increasingly vital role in ensuring product quality. With the growing complexity of device architectures, traditional inspection approaches are increasingly challenged. AI and machine vision offer scalable solutions for identifying defects, interpreting visual patterns, and automating inspection tasks across multiple stages of semiconductor production.
Join this webinar to see practical, engineering-oriented methods for applying AI to visual inspection workflows to improve accuracy, consistency, and overall manufacturing yield.
Highlights
In this webinar, you will see:
- Techniques for image preprocessing, feature extraction, and segmentation
- A demonstration of how deep learning can be used for object detection, classification, and anomaly detection.
- How deep learning models and traditional vision algorithms can be combined to create robust inspection solutions
About the Presenter
John Gawedzinski
Senior Application Engineer | MathWorks
John is a Senior Application Engineer at MathWorks supporting the medical devices and digital health sector. He received his B.S. in Biomedical Engineering from Boston University and a Ph.D. in Bioengineering from Rice University with a focus in applied optics and medical imaging. Before joining MathWorks, John worked as an Optical Engineer at Spectral AI specializing in multispectral stereo vision systems that use predictive AI algorithms to evaluate wound healing. Prior to his graduate studies, John worked at Epic Systems as a Technical Services Engineer supporting technical customer needs related to electronic health records.
This event is part of a series of related topics. View the full list of events in this series.
