From 0bede27de3bcc0c7f03d16c7607a0ae693daebc7 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Mon, 1 Apr 2019 10:23:29 +0200 Subject: citations table in react --- site/includes/citations.html | 2 +- site/public/datasets/index.html | 12 +++ site/public/datasets/msceleb/index.html | 143 ++++++++++++++++++++++++++++++++ 3 files changed, 156 insertions(+), 1 deletion(-) create mode 100644 site/public/datasets/msceleb/index.html (limited to 'site') diff --git a/site/includes/citations.html b/site/includes/citations.html index 058a1834..d29812df 100644 --- a/site/includes/citations.html +++ b/site/includes/citations.html @@ -6,7 +6,7 @@ and indexes research papers. The citations were geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train and/or test machine learning algorithms.

- Add [button/link] to download CSV. Add search input field to filter. Expand number of rows to 10. Reduce URL text to show only the domain (ie https://arxiv.org/pdf/123456 --> arxiv.org) + Add [button/link] to download CSV. Add search input field to filter.

diff --git a/site/public/datasets/index.html b/site/public/datasets/index.html index f618e86b..03b38f8a 100644 --- a/site/public/datasets/index.html +++ b/site/public/datasets/index.html @@ -85,6 +85,18 @@ + +
+ MS Celeb +
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2016
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face recognition
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1,000,000 images
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100,000
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People in Photo Albums diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html new file mode 100644 index 00000000..8ebfe1a4 --- /dev/null +++ b/site/public/datasets/msceleb/index.html @@ -0,0 +1,143 @@ + + + + MegaPixels + + + + + + + + + + + + +
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MegaPixels
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+ Datasets + About +
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MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms
The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine +
Published
TBD
Images
TBD
Faces
TBD
Created by
TBD

Microsoft Celeb Dataset (MS Celeb)

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(PAGE UNDER DEVELOPMENT)

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Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

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Who used MsCeleb?

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+ This bar chart presents a ranking of the top countries where citations originated. Mouse over individual columns + to see yearly totals. These charts show at most the top 10 countries. +

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+ These pie charts show overall totals based on country and institution type. +

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Information Supply Chain

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+ To understand how MsCeleb has been used around the world... + affected global research on computer vision, surveillance, defense, and consumer technology, the and where this dataset has been used the locations of each organization that used or referenced the datast +

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  • Academic
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  • Government / Military
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  • Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
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+ [section under development] MsCeleb ... Standardized paragraph of text about the map. Sed ut perspiciatis, unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam eaque ipsa, quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt, explicabo. +

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Add more analysis here

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Supplementary Information

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Citations

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+ Citations were collected from Semantic Scholar, a website which aggregates + and indexes research papers. The citations were geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train and/or test machine learning algorithms. +

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+ Add [button/link] to download CSV. Add search input field to filter. Expand number of rows to 10. Reduce URL text to show only the domain (ie https://arxiv.org/pdf/123456 --> arxiv.org) +

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Additional Information

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  • "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385.

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  • Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598.

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  • Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.

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