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Claire McQuin

Showing results (1-10 of 9) with videos related to

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Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition|March 29, 2019
Weakly Supervised Learning of Single-Cell Feature EmbeddingsJuan C Caicedo, Claire McQuin, Allen Goodman, et al.
Nature Protocols|June 19, 2021
Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometryMinh Doan, Claire Barnes, Claire McQuin, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|July 18, 2019
Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence ImagesJuan C Caicedo, Jonathan Roth, Allen Goodman, et al.
Nature Methods|January 24, 2020
Publisher Correction: Nucleus segmentation across imaging experiments: the 2018 Data Science BowlJuan C Caicedo, Allen Goodman, Kyle W Karhohs, et al.
Nature Methods|October 23, 2019
Nucleus segmentation across imaging experiments: the 2018 Data Science BowlJuan C Caicedo, Allen Goodman, Kyle W Karhohs, et al.
Nature Communications|February 21, 2024
Learning representations for image-based profiling of perturbationsNikita Moshkov, Michael Bornholdt, Santiago Benoit, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|February 25, 2020
Label-Free Leukemia Monitoring by Computer VisionMinh Doan, Marian Case, Dino Masic, et al.
Plos Biology|July 4, 2018
CellProfiler 3.0: Next-generation image processing for biologyClaire McQuin, Allen Goodman, Vasiliy Chernyshev, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 26, 2020
Objective assessment of stored blood quality by deep learningMinh Doan, Joseph A Sebastian, Juan C Caicedo, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition|March 29, 2019
Weakly Supervised Learning of Single-Cell Feature EmbeddingsJuan C Caicedo, Claire McQuin, Allen Goodman, et al.
Nature Protocols|June 19, 2021
Deepometry, a framework for applying supervised and weakly supervised deep learning to imaging cytometryMinh Doan, Claire Barnes, Claire McQuin, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|July 18, 2019
Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence ImagesJuan C Caicedo, Jonathan Roth, Allen Goodman, et al.
Nature Methods|January 24, 2020
Publisher Correction: Nucleus segmentation across imaging experiments: the 2018 Data Science BowlJuan C Caicedo, Allen Goodman, Kyle W Karhohs, et al.
Nature Methods|October 23, 2019
Nucleus segmentation across imaging experiments: the 2018 Data Science BowlJuan C Caicedo, Allen Goodman, Kyle W Karhohs, et al.
Nature Communications|February 21, 2024
Learning representations for image-based profiling of perturbationsNikita Moshkov, Michael Bornholdt, Santiago Benoit, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|February 25, 2020
Label-Free Leukemia Monitoring by Computer VisionMinh Doan, Marian Case, Dino Masic, et al.
Plos Biology|July 4, 2018
CellProfiler 3.0: Next-generation image processing for biologyClaire McQuin, Allen Goodman, Vasiliy Chernyshev, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 26, 2020
Objective assessment of stored blood quality by deep learningMinh Doan, Joseph A Sebastian, Juan C Caicedo, et al.
Pageof 1