Exploring Benchmarks for Self-Driving Labs using Color Matching-Reference-Cited by-同舟云学术

Exploring Benchmarks for Self-Driving Labs using Color Matching

Published:2023-11-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis
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Author:

Ginsburg Tobias¹^ORCID,Hippe Kyle²^ORCID,Lewis Ryan³^ORCID,Cleary Aileen⁴^ORCID,Ozgulbas Doga²^ORCID,Butler Rory⁵^ORCID,Stone Casey²^ORCID,Stroka Abraham²^ORCID,Vescovi Rafael¹^ORCID,Foster Ian¹^ORCID

Affiliation:

1. Argonne National Laboratory (ANL), Data Science and Learning Division, United States of America

2. Argonne National Laboratory (ANL), United States of America

3. Argonne National Laboratory (ANL), USA

4. Northwestern University, United States of America

5. University of Chicago, United States of America

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624062.3624615

Reference15 articles.

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2. Building a “Hello World” for self-driving labs: The Closed-loop Spectroscopy Lab Light-mixing demo

3. G. Bradski . 2000. The OpenCV Library. Dr. Dobb’s Journal of Software Tools ( 2000 ). G. Bradski. 2000. The OpenCV Library. Dr. Dobb’s Journal of Software Tools (2000).

4. Globus automation services: Research process automation across the space–time continuum

5. Automatic generation and detection of highly reliable fiducial markers under occlusion