File:Deep-Learning-Automates-the-Quantitative-Analysis-of-Individual-Cells-in-Live-Cell-Imaging-pcbi.1005177.s025.ogv

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Original file (Ogg Theora video file, length 6.4 s, 1,280 × 1,080 pixels, 15.35 Mbps, file size: 11.76 MB)

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English: Representative movie of HeLa-S3 with overlaying nuclear marker and segmentation boundaries.
Date
Source S7 Movie from Van Valen D, Kudo T, Lane K, Macklin D, Quach N, DeFelice M, Maayan I, Tanouchi Y, Ashley E, Covert M (2016). "Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments". PLOS Computational Biology. DOI:10.1371/journal.pcbi.1005177. PMID 27814364. PMC: 5096676.
Author Van Valen D, Kudo T, Lane K, Macklin D, Quach N, DeFelice M, Maayan I, Tanouchi Y, Ashley E, Covert M
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This file is licensed under the Creative Commons Attribution 4.0 International license.
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This file was transferred to Wikimedia Commons from PubMed Central by way of the Open Access Media Importer.
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Date/TimeThumbnailDimensionsUserComment
current12:23, 31 January 20176.4 s, 1,280 × 1,080 (11.76 MB)Open Access Media Importer Bot (talk | contribs)Automatically uploaded media file from Open Access source. Please report problems or suggestions here.

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Format Bitrate Download Status Encode time
VP9 1080P 5.12 Mbps Completed 18:47, 23 August 2018 14 s
VP9 720P 2.56 Mbps Completed 18:47, 23 August 2018 10 s
VP9 480P 1.23 Mbps Completed 18:46, 23 August 2018 7.0 s
VP9 360P 635 kbps Completed 18:46, 23 August 2018 6.0 s
VP9 240P 299 kbps Completed 18:46, 23 August 2018 4.0 s
WebM 360P 514 kbps Completed 12:23, 31 January 2017 5.0 s
QuickTime 144p (MJPEG) 636 kbps Completed 01:07, 22 October 2024 1.0 s

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