Defect Inspection 2
Chairs: Alexa Greer, Oliver Patterson
In-line inspection is critical for modern semiconductor processing. The session talks about defect inspection/review for yield improvement for a wide range of use cases. DI2 discusses new applications/methodologies for process characterization and defect classification.
Wednesday, May 4, 2022
9:20 AM ET
7.1 Full Wafer Process Control Through Object Detection Using Region-Based Convolutional Neural Networks.
T. Alcaire, V. Brouzet, R. Duru, C. Euvard, D. Le Cunff, STMicroelectronics; JH. Tortai, S. Soulan, University of Grenoble, Alpes
9:45
7.2 Photoluminescence Imaging for Slip Line Detection and Characterization in Silicon Substrates.
Romain Duru, Isabella Mica, Jacopo Frascaroli, STMicroelecronics; Pierre Bellanger, Semilab
10:10
7.3 Automatic Wafer Defect Classification Based on Decision Tree of Deep Neural Networks.
Zhixing Li, Weiping Shi, Texas A&M; Zhangyang Wang, University of Texas at Austin
10:35
7.4 Hybrid Quantum-Classical Machine Learning for Lithography Hotspot Detection.
YuanFu Yang, Min Sun, National Tsing Hua University
11:00
7.5 On-Wafer Organic Defect Review and Classification with Universal Surface Enhanced Raman Spectroscopy.
Ali Altun, UNISERS Ltd