Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-26T07:55:20.248Z Has data issue: false hasContentIssue false

Development of a Flexible Ensemble Classification System for Microscopy

Published online by Cambridge University Press:  22 July 2022

Tomas J. McIntee
Affiliation:
Ion Innovations, Boone, NC, United States.
Mathieu Therezien
Affiliation:
Ion Innovations, Boone, NC, United States.
Zachary E. Russell*
Affiliation:
Ion Innovations, Boone, NC, United States.
*
*Corresponding author: [email protected]

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

Russell, Z et al. , Appalachian Regional Microscopy Society (AReMS) Annual Meeting (2019).Google Scholar
Zhang, Y et al. , Sensors 19 (2019), p. 3914. doi:10.3390/s19183914CrossRefGoogle ScholarPubMed
Mohapatra, S et al. , Neural Computing and Applications 24 (2014), p. 1887. doi:10.1007/s00521-013-1438-3CrossRefGoogle Scholar
Rashidi, M and Wolkow, R, ACS Nano 12 (2018), p. 5185. doi:10.1021/acsnano.8b02208CrossRefGoogle Scholar
Rokach, L in “Data Mining and Knowledge Discovery Handbook”, eds Maimon, O, Rokach, L, (Springer, Boston), p. 957.Google Scholar
Gandhi, I and Pandey, M, International Conference on Green Computing and Internet of Things (2015), p. 399.Google Scholar
Bauer, E and Kohavi, R, Machine Learning 36 (1999), p.105. doi:10.1023/A:1007515423169CrossRefGoogle Scholar
Tumer, K and Ghosh, J, Connection Science 8 (1996), p. 385. doi:10.1080/095400996116839CrossRefGoogle Scholar
Rokach, L, Artificial Intelligence Review 33 (2010), p.1. doi:10.1007/s10462-009-9124-7CrossRefGoogle Scholar