Session 3—Defect Inspection I
Chairs: Alexa Greer, KLA; Israel Ne’eman, Applied Materials; Alex Varghese, IBM Research; Abhishek Vikram, Anchor Semiconductor
The session includes papers on SEM inspection and review followed by two applications of deep learning for defect generation and classification.
3.1 Creative Use of Vector Scan for Efficient SRAM Inspection
Oliver D. Patterson, Hsiao-Chi Peng, Haokun Hu, Hermes Microvision (An ASML company); Chih-Chung Huang, GLOBALFOUNDRIES
3.2 Analysis of Systematic Weak Point Structures using Design Based Automatic Defect Classification and Defect Review SEM Platform
Teresa A. Esposito, Felix Levitov, Applied Materials; Shi-Hui Jen, Qian Xie, Danda Acharya, Julie Lee, GLOBALFOUNDRIES
3.3 Electron Beam Inspection: Voltage Contrast Inspection to Characterize Contact Isolation
Richard F. Hafer, Andrew Stamper, GLOBALFOUNDRIES; Jerry Hsieh, Hermes Microvision Inc.
3.4 Double Feature Extraction Method for Wafer Map Classification Based on Convolution Neural Network
Yuan-Fu Yang, Min Sun, National Tsing Hua University (Student)
3.5 Generative Adversarial Networks for Synthetic Defect Generation in Assembly and Test Manufacturing
Rajhans Singh, Arizona State University and Intel; Ravi Garg, Nital S. Patel, Martin W. Braun, Intel Corporation