no code implementations • 18 Nov 2023 • Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt
We discuss the advantages and disadvantages of different feature extractors as well as the RL-based framework in general for semiconductor defect localization.
no code implementations • 16 Aug 2023 • Thibault Lechien, Enrique Dehaerne, Bappaditya Dey, Victor Blanco, Sandip Halder, Stefan De Gendt, Wannes Meert
This inherent noise is one of the main challenges for defect inspection.
no code implementations • 14 Aug 2023 • Vic De Ridder, Bappaditya Dey, Enrique Dehaerne, Sandip Halder, Stefan De Gendt, Bartel Van Waeyenberge
We have proposed SEMI-CenterNet (SEMI-CN), a customized CN architecture trained on SEM images of semiconductor wafer defects.
no code implementations • 28 Jul 2023 • Enrique Dehaerne, Bappaditya Dey, Hossein Esfandiar, Lander Verstraete, Hyo Seon Suh, Sandip Halder, Stefan De Gendt
In this work, we propose a method for obtaining coherent and complete labels for a dataset of hexagonal contact hole DSA patterns while requiring minimal quality control effort from a DSA expert.
1 code implementation • 26 Apr 2023 • Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt
This is validated by comparing different pretrained models trained on different subsets of the proposed Verilog dataset using multiple evaluation metrics.
no code implementations • 19 Feb 2023 • Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt
In this research, we experiment with YOLOv7, a recently proposed, state-of-the-art object detector, by training and evaluating models with different hyperparameters to investigate which ones improve performance in terms of detection precision for semiconductor line space pattern defects.