most citedOptimizing YOLOv7 for Semiconductor Defect Detection

20 citations · 57 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20231 cited

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…

cs.CV20234 cited

Automated Semiconductor Defect Inspection in Scanning Electron Microscope Images: a Systematic Review

Thibault Lechien, Enrique Dehaerne, Bappaditya Dey +4

A growing need exists for efficient and accurate methods for detecting defects in semiconductor materials and devices. These defects can have a detrimental impact on the efficiency…

cs.CV20232 cited

SEMI-CenterNet: A Machine Learning Facilitated Approach for Semiconductor Defect Inspection

Vic De Ridder, Bappaditya Dey, Enrique Dehaerne +3

Continual shrinking of pattern dimensions in the semiconductor domain is making it increasingly difficult to inspect defects due to factors such as the presence of stochastic noise…

cs.CV202316 cited

YOLOv8 for Defect Inspection of Hexagonal Directed Self-Assembly Patterns: A Data-Centric Approach

Enrique Dehaerne, Bappaditya Dey, Hossein Esfandiar +4

Shrinking pattern dimensions leads to an increased variety of defect types in semiconductor devices. This has spurred innovation in patterning approaches such as Directed self-asse…

cs.LG20232 cited

A Deep Learning Framework for Verilog Autocompletion Towards Design and Verification Automation

Enrique Dehaerne, Bappaditya Dey, Sandip Halder +1

Innovative Electronic Design Automation (EDA) solutions are important to meet the design requirements for increasingly complex electronic devices. Verilog, a hardware description l…

cs.CV202312 cited

SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation as Rendering

MinJin Hwang, Bappaditya Dey, Enrique Dehaerne +2

In this study, we applied the PointRend (Point-based Rendering) method to semiconductor defect segmentation. PointRend is an iterative segmentation algorithm inspired by image rend…