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IEEE1mon
AI-Powered Defect Detection using Deep Learning: A Pattern-Agnostic Faster R-CNN Approach for SEM Images with GPU Acceleration
Semiconductor manufacturing requires highly precise defect detection to ensure product quality and yield. This paper presents a deep learning-based defect detection framework using Faster R-CNN to ...
Semiconductor Engineering5y
Fast LFD Flows With Pattern Matching And Machine Learning Can Deliver Higher-Yielding Designs Faster - Semiconductor Engineering
Machine learning FLFD flow vs. pattern matching FLFD flow. Pattern matching FLFD By inserting a PM operation before simulation, designers can create a fast LFD ... “Accurate lithography hotspot ...
Semiconductor Engineering2y
Identifying PCB Defects with a Deep Learning Single-Step Detection Model - Semiconductor Engineering
This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...
C&EN1mon
Simple and Multiplexed Detection of Nucleic Acid Targets Based on Fluorescent Ring Patterns and Deep Learning Analysis | ACS Applied Materials & Interfaces - ACS Publications
Simple diagnostic tests for nucleic acid targets can provide great advantages for applications such as rapid pathogen detection. Here, we developed a membrane assay for multiplexed detection of ...
IEEE1mon
AI-Powered Defect Detection using Deep Learning: A Pattern-Agnostic Faster R-CNN Approach for SEM Images with GPU Acceleration - IEEE Xplore
Semiconductor manufacturing requires highly precise defect detection to ensure product quality and yield. This paper presents a deep learning-based defect detection framework using Faster R-CNN to ...