Vladimir Shlain

Title: Innovations of Vladimir Shlain

Introduction

Vladimir Shlain is a notable inventor based in Haifa, Israel. He has made significant contributions to the field of automatic defect classification, holding a total of 3 patents. His work focuses on optimizing defect rejection processes, which are crucial in various manufacturing and inspection industries.

Latest Patents

One of his latest patents is titled "Optimization of unknown defect rejection for automatic defect classification." This method involves storing a definition of a region in a feature space associated with a class of defects. It utilizes a kernel function with a parameter that determines the shape of the region. The method also includes receiving a confidence threshold for automatic classification of defects and selecting a value of the parameter based on this threshold. The inspection data for multiple defects is then classified automatically using the kernel function.

Another significant patent is "Classifier readiness and maintenance in automatic defect classification." This method includes receiving inspection data related to various defects and benchmark classifications for these defects. A readiness criterion is evaluated based on the benchmark results, determining the suitability of the inspection data for training an automatic defect classifier. The method allows for the selection of inspection data corresponding to defects that meet the readiness criterion, enabling the training of automatic classifiers.

Career Highlights

Vladimir Shlain is currently employed at Applied Materials Israel Limited, where he continues to innovate in the field of defect classification. His expertise and contributions have positioned him as a key figure in his organization.

Collaborations

He has collaborated with notable coworkers, including Idan Kaizerman and Efrat Rozenman, who share his commitment to advancing technology in defect classification.

Conclusion

Vladimir Shlain's work in automatic defect classification showcases his innovative spirit and dedication to improving manufacturing processes. His patents reflect a deep understanding of the complexities involved in defect detection and classification.