mlsanityData to 7 Oct 2026

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

arXiv 2302.09569 ↗First posted 19 Feb 2023cs.CVcited by 3

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Abstract (arXiv)

In this study, we applied the PointRend (Point-based Rendering) method to semiconductor defect segmentation. PointRend is an iterative segmentation algorithm inspired by image rendering in computer graphics, a new image segmentation method that can generate high-resolution segmentation masks. It can also be flexibly integrated into common instance segmentation meta-architecture such as Mask-RCNN and semantic meta-architecture such as FCN. We implemented a model, termed as SEMI-PointRend, to generate precise segmentation masks by applying the PointRend neural network module. In this paper, we focus on comparing the defect segmentation predictions of SEMI-PointRend and Mask-RCNN for various defect types (line-collapse, single bridge, thin bridge, multi bridge non-horizontal). We show that SEMI-PointRend can outperforms Mask R-CNN by up to 18.8% in terms of segmentation mean average precision.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 9 of its 14 references that are in the map. First posted on arXiv 19 Feb 2023.

Builds on

9 of 14 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  5. 2017Mask R-CNNcited by 7,259
  6. 2019PointRend: Image Segmentation as Renderingcited by 439
  7. 2019The VIA Annotation Software for Images, Audio and Videocited by 166
  8. 2022Deep Learning-Based Defect Classification and Detection in SEM Imagescited by 14
  9. 2022Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approachcited by 8

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Cited by year

Citing papers per year: 2023: 2; 2024: 1.

3 papers.

  1. 2023SEMI-DiffusionInst: A Diffusion Model Based Approach for Semiconductor Defect Classification and Segmentationcited by 3
  2. 2023Benchmarking Feature Extractors for Reinforcement Learning-Based Semiconductor Defect Localizationcited by 0
  3. 2024Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodescited by 0