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DualSight: multi-stage instance segmentation framework for improved precision.

Stephen Price1, Kiran Judd2, Kyle Tsaknopoulos2

  • 1Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, 01609, USA. sprice@wpi.edu.

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|July 28, 2025
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Summary
This summary is machine-generated.

DualSight enhances metallic powder segmentation for cold spray additive manufacturing. This computer vision framework improves powder morphology analysis accuracy without needing more data or retraining.

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Area of Science:

  • Materials Science
  • Additive Manufacturing
  • Computer Vision

Background:

  • Powder morphology significantly impacts cold spray additive manufacturing quality, affecting flowability, deposition, and porosity.
  • Manual image analysis of powder morphology is time-consuming and labor-intensive.
  • Automated computer vision methods for powder analysis are limited by training data quality.

Purpose of the Study:

  • To present DualSight, a novel multi-stage computer vision framework.
  • To improve metallic powder segmentation quality for morphology analysis.
  • To enable more accurate powder characterization without additional data or model training.

Main Methods:

  • Development of a multi-stage computer vision framework named DualSight.
  • Application of the framework to segment metallic powders from scanning electron microscope images.
  • Evaluation of segmentation quality improvements without new data or retraining.

Main Results:

  • DualSight demonstrates improved metallic powder segmentation quality.
  • The framework enhances the accuracy of powder morphology extraction.
  • Accurate morphology data facilitates better-informed manufacturing decisions.

Conclusions:

  • DualSight offers a data-efficient approach to improve powder morphology analysis in additive manufacturing.
  • Enhanced segmentation accuracy leads to better understanding and control of cold spray processes.
  • This framework supports more reliable and efficient additive manufacturing of metallic materials.