371 to 380 of 20,418 Results
Apr 15, 2024 -
GLOBALISE Laypa Baseline Model – August 2023
Unknown - 434.3 MB -
MD5: 9073a4c3a5e79d733aca72689a262168
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Apr 11, 2024 - GLOBALISE
Nijman, Brecht, 2024, "GLOBALISE Geographical Indices of the RGP General Missives", https://hdl.handle.net/10622/75DURG, IISH Data Collection, V1, UNF:6:cFqs57joFthWFOBHbue99A== [fileUNF]
This dataset presents the geographical indices of the 14 volumes of the RGP editions of the Generale Missiven der V.O.C. (GM) (1960-2007) in a structured format. The RGP General Missiven are a published selection of the General Letters from the period 1610 to 1767. These were sum... |
Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Adobe PDF - 107.5 KB -
MD5: 52b314b0cc33195add1e34b4d7761ec3
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Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Plain Text - 271.9 KB -
MD5: a2313d4906d12c2c3884b9ccdebee588
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Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Tabular Data - 1.2 MB - 6 Variables, 8948 Observations - UNF:6:2LAsGcilHi6bb7Ixg+LVRg==
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Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Python Source Code - 9.0 KB -
MD5: 59baf529751235b9e71af17fad399d7e
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Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Tabular Data - 1.2 MB - 6 Variables, 8978 Observations - UNF:6:1iExMYvub9VC/JGYJsZMHg==
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Apr 11, 2024 -
GLOBALISE Geographical Indices of the RGP General Missives
Markdown Text - 6.8 KB -
MD5: 7429a7c03b5c9fa3c58dff852e2112fa
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Apr 11, 2024 - GLOBALISE
Klut, Stefan; Koert, Rutger van; Maas, Martijn, 2024, "GLOBALISE Laypa Region Model - August 2023", https://hdl.handle.net/10622/DMAS2T, IISH Data Collection, V1
This is a Laypa region detection model that was created to detect and identify regions (such as page number, heading, paragraph, and marginalia) on the scans of the GLOBALISE VOC corpus. It was trained on Ground Truth that is also available in this Dataverse (GLOBALISE Ground Tru... |
Apr 11, 2024 -
GLOBALISE Laypa Region Model - August 2023
Unknown - 8.9 KB -
MD5: f125e928160cd408b40b59522486abf6
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