SensiCut: Material-Aware Laser Cutting Using Speckle Sensing and Deep Learning

Author:

Dogan Mustafa Doga1,Acevedo Colon Steven Vidal1,Sinha Varnika1,Akşit Kaan2,Mueller Stefanie1

Affiliation:

1. MIT CSAIL, United States

2. Computer Science University College London, United Kingdom

Funder

MIT Portugal Initiative

NSF

MIT Mechanical Engineering MathWorks Seed Fund Program

Publisher

ACM

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Structured Light Speckle: Joint Ego-Centric Depth Estimation and Low-Latency Contact Detection via Remote Vibrometry;Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology;2023-10-29

2. BrightMarker: 3D Printed Fluorescent Markers for Object Tracking;Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology;2023-10-29

3. StructCode: Leveraging Fabrication Artifacts to Store Data in Laser-Cut Objects;Proceedings of the 8th ACM Symposium on Computational Fabrication;2023-10-08

4. Material Classification in Laser Cutting using Deep Learning;2023 Intelligent Methods, Systems, and Applications (IMSA);2023-07-15

5. Kerfmeter: Automatic Kerf Calibration for Laser Cutting;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

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