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File:Deep-Learning-Automates-the-Quantitative-Analysis-of-Individual-Cells-in-Live-Cell-Imaging-pcbi.1005177.s020.ogv

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Original file (Ogg Theora video file, length 2.7 s, 900 × 900 pixels, 5.79 Mbps, file size: 1.87 MB)

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English: Bacteria-net output when used to process S1 Movie .
Date
Source S2 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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Date/TimeThumbnailDimensionsUserComment
current12:21, 31 January 20172.7 s, 900 × 900 (1.87 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 720P 2.27 Mbps Completed 00:43, 25 February 2026 5.0 s
VP9 480P 1.28 Mbps Completed 00:43, 25 February 2026 3.0 s
VP9 360P 685 kbps Completed 00:43, 25 February 2026 4.0 s
VP9 240P 344 kbps Completed 00:43, 25 February 2026 3.0 s
WebM 360P 547 kbps Completed 00:19, 25 February 2026 1.0 s
QuickTime 144p (MJPEG) 613 kbps Completed 02:22, 25 February 2026 1.0 s

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