Abstract
Recognition and Visualization of Lithography Defects based on Transfer Learning
Highlights
Defect reduction is critical during the integrated circuit (IC) manufacturing process
Grad-CAM can realize the autonomous location of defects, which is of great significance for improving the automatic control system of integrated circuit manufacturing
We first demonstrated the recognition and classification of several lithography defects based on transfer learning
Summary
Defect reduction is critical during the integrated circuit (IC) manufacturing process. Through the continuous shrinking of the process, the defect control is becoming more and more stringent, which prompt engineers to use low-magnification and large field of view electronic scanning technology, and perform rapid comparison through spatial feature analysis [2]. The limitation of this method is that the types of defect cannot be automatically classified, and the size of the identifiable defect be greatly restricted. This method will be used to improve the existing defect detection system in the field of IC manufacturing and improve the efficiency of autonomous identification
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