2 citations · 4 across the 11 of their papers we have counts for
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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…
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…
Benchmarking Feature Extractors for Reinforcement Learning-Based Semiconductor Defect Localization
Enrique Dehaerne, Bappaditya Dey, Sandip Halder +1
As semiconductor patterning dimensions shrink, more advanced Scanning Electron Microscopy (SEM) image-based defect inspection techniques are needed. Recently, many Machine Learning…
Deep learning denoiser assisted roughness measurements extraction from thin resists with low Signal-to-Noise Ratio(SNR) SEM images: analysis with SMILE
Sara Sacchi, Bappaditya Dey, Iacopo Mochi +2
The technological advance of High Numerical Aperture Extreme Ultraviolet Lithography (High NA EUVL) has opened the gates to extensive researches on thinner photoresists (below 30nm…