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

16 citations · 19 across the 7 of their papers we have counts for

collaborators

7 papers

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.…

cs.CV2023

Improved Defect Detection and Classification Method for Advanced IC Nodes by Using Slicing Aided Hyper Inference with Refinement Strategy

Vic De Ridder, Bappaditya Dey, Victor Blanco +2

In semiconductor manufacturing, lithography has often been the manufacturing step defining the smallest possible pattern dimensions. In recent years, progress has been made towards…

eess.SP2023

Applying Machine Learning Models on Metrology Data for Predicting Device Electrical Performance

Bappaditya Dey, Anh Tuan Ngo, Sara Sacchi +3

Moore Law states that transistor density will double every two years, which is sustained until today due to continuous multi-directional innovations, such as extreme ultraviolet li…