GLAM-Workbench/facial-detection

Research output: Non-textual formSoftware

Abstract

Notebooks using facial detection to explore images from the Tribune negative collection in the State Library of NSW.
Original languageEnglish
Place of PublicationSwitzerland
PublisherZenodo - CERN (European Organisation for Nuclear Research)
DOIs
Publication statusPublished - 21 Nov 2019

Cite this

Sherratt, T. (Author). (2019). GLAM-Workbench/facial-detection. Software, Switzerland: Zenodo - CERN (European Organisation for Nuclear Research). https://doi.org/10.5281/zenodo.3549147
@misc{538e68eec1654bfe88fc0fdd2b945502,
title = "GLAM-Workbench/facial-detection",
abstract = "Notebooks using facial detection to explore images from the Tribune negative collection in the State Library of NSW.",
author = "Tim Sherratt",
year = "2019",
month = "11",
day = "21",
doi = "10.5281/zenodo.3549147",
language = "English",
publisher = "Zenodo - CERN (European Organisation for Nuclear Research)",

}

Sherratt, T, GLAM-Workbench/facial-detection, 2019, Software, Zenodo - CERN (European Organisation for Nuclear Research), Switzerland. https://doi.org/10.5281/zenodo.3549147
GLAM-Workbench/facial-detection. Sherratt, Tim (Author). 2019. Switzerland : Zenodo - CERN (European Organisation for Nuclear Research).

Research output: Non-textual formSoftware

TY - ADVS

T1 - GLAM-Workbench/facial-detection

AU - Sherratt, Tim

PY - 2019/11/21

Y1 - 2019/11/21

N2 - Notebooks using facial detection to explore images from the Tribune negative collection in the State Library of NSW.

AB - Notebooks using facial detection to explore images from the Tribune negative collection in the State Library of NSW.

UR - https://glam-workbench.github.io/facial-detection/

U2 - 10.5281/zenodo.3549147

DO - 10.5281/zenodo.3549147

M3 - Software

PB - Zenodo - CERN (European Organisation for Nuclear Research)

CY - Switzerland

ER -

Sherratt T (Author). GLAM-Workbench/facial-detection Switzerland: Zenodo - CERN (European Organisation for Nuclear Research). 2019. https://doi.org/10.5281/zenodo.3549147