activity
20222026
most citedDeep Learning-Based Defect Classification and Detection in SEM Images

33 citations · 112 across the 23 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024★ 1 cited

Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodes

Bappaditya Dey, Matthias Monden, Victor Blanco +2

In this research, we introduce a unified end-to-end Automated Defect Classification-Detection-Segmentation (ADCDS) framework for classifying, detecting, and segmenting multiple ins…

eess.IV2024★ 16 cited

Scanning Electron Microscopy-based Automatic Defect Inspection for Semiconductor Manufacturing: A Systematic Review

Enrique Dehaerne, Bappaditya Dey, Victor Blanco +1

In this review, automatic defect inspection algorithms that analyze Scanning Electron Microscopy (SEM) images for Semiconductor Manufacturing (SM) are identified, categorized, and…

cs.CV2024

An Evaluation of Continual Learning for Advanced Node Semiconductor Defect Inspection

Amit Prasad, Bappaditya Dey, Victor Blanco +1

Deep learning-based semiconductor defect inspection has gained traction in recent years, offering a powerful and versatile approach that provides high accuracy, adaptability, and e…

cs.CV2024★ 2 cited

Addressing Class Imbalance and Data Limitations in Advanced Node Semiconductor Defect Inspection: A Generative Approach for SEM Images

Bappaditya Dey, Vic De Ridder, Victor Blanco +2

Precision in identifying nanometer-scale device-killer defects is crucial in both semiconductor research and development as well as in production processes. The effectiveness of ex…

cs.CV2024

Towards Improved Semiconductor Defect Inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS

Ying-Lin Chen, Jacob Deforce, Vic De Ridder +4

Due to potential pitch reduction, the semiconductor industry is adopting High-NA EUVL technology. However, its low depth of focus presents challenges for High Volume Manufacturing.…