Machine Generated Data
Tags
Amazon
created on 2023-10-25
Clarifai
created on 2018-10-06
Imagga
created on 2018-10-06
shuttlecock | 59.8 | |
| ||
quill | 27 | |
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pen | 26.7 | |
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architecture | 18.7 | |
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yacht | 17.5 | |
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vessel | 17.4 | |
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writing implement | 15.6 | |
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newspaper | 14.2 | |
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city | 14.1 | |
| ||
business | 14 | |
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structure | 13.7 | |
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sky | 13.4 | |
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office | 13 | |
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paper | 12.5 | |
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tower | 12.5 | |
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building | 12.4 | |
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water | 10.7 | |
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urban | 10.5 | |
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industry | 10.2 | |
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people | 10 | |
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old | 9.8 | |
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information | 9.7 | |
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construction | 9.4 | |
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write | 9.4 | |
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hand | 9.1 | |
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landmark | 9 | |
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design | 9 | |
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boat | 8.8 | |
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sail | 8.8 | |
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product | 8.7 | |
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work | 8.6 | |
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writing | 8.5 | |
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modern | 8.4 | |
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power | 8.4 | |
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weapon | 8.2 | |
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object | 8.1 | |
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missile | 7.9 | |
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sailing | 7.8 | |
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wind | 7.5 | |
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person | 7.5 | |
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monument | 7.5 | |
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silhouette | 7.4 | |
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document | 7.4 | |
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light | 7.4 | |
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transport | 7.3 | |
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obelisk | 7.3 | |
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success | 7.2 | |
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craft | 7.1 | |
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travel | 7 | |
|
Google
created on 2018-10-06
black and white | 95.1 | |
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black | 95 | |
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monochrome photography | 91.4 | |
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photography | 83.8 | |
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monochrome | 73.8 | |
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angle | 54.8 | |
|
Color Analysis
Feature analysis
Categories
Imagga
Captions
Microsoft
created on 2018-10-06
a screenshot of a computer | 53.6% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/38979114/921,543,44,66/full/0/native.jpg)
12
![](https://ids.lib.harvard.edu/ids/iiif/38979114/49,2993,45,199/full/0/native.jpg)
KODAK
![](https://ids.lib.harvard.edu/ids/iiif/38979114/911,2488,42,69/full/0/native.jpg)
10
![](https://ids.lib.harvard.edu/ids/iiif/38979114/50,3279,42,227/full/0/native.jpg)
SAFETY
![](https://ids.lib.harvard.edu/ids/iiif/38979114/921,1051,40,85/full/0/native.jpg)
11A
![](https://ids.lib.harvard.edu/ids/iiif/38979114/911,3015,48,87/full/0/native.jpg)
9A
![](https://ids.lib.harvard.edu/ids/iiif/38979114/901,4992,50,91/full/0/native.jpg)
7A
![](https://ids.lib.harvard.edu/ids/iiif/38979114/58,1091,36,101/full/0/native.jpg)
TRI
![](https://ids.lib.harvard.edu/ids/iiif/38979114/915,1991,44,107/full/0/native.jpg)
10A
![](https://ids.lib.harvard.edu/ids/iiif/38979114/54,836,42,448/full/0/native.jpg)
KODAK TRI x
![](https://ids.lib.harvard.edu/ids/iiif/38979114/903,4523,44,36/full/0/native.jpg)
8
![](https://ids.lib.harvard.edu/ids/iiif/38979114/902,4009,50,89/full/0/native.jpg)
BA
![](https://ids.lib.harvard.edu/ids/iiif/38979114/54,1359,42,308/full/0/native.jpg)
by
![](https://ids.lib.harvard.edu/ids/iiif/38979114/60,1252,32,32/full/0/native.jpg)
x
![](https://ids.lib.harvard.edu/ids/iiif/38979114/909,3537,38,32/full/0/native.jpg)
o
![](https://ids.lib.harvard.edu/ids/iiif/38979114/226,3020,90,31/full/0/native.jpg)
USANSA
![](https://ids.lib.harvard.edu/ids/iiif/38979114/43,3587,48,167/full/0/native.jpg)
$ 100
![](https://ids.lib.harvard.edu/ids/iiif/38979114/909,2485,52,1613/full/0/native.jpg)
8
OL
y 6
![](https://ids.lib.harvard.edu/ids/iiif/38979114/909,4057,37,39/full/0/native.jpg)
8
![](https://ids.lib.harvard.edu/ids/iiif/38979114/913,2485,46,69/full/0/native.jpg)
OL
![](https://ids.lib.harvard.edu/ids/iiif/38979114/913,3013,43,39/full/0/native.jpg)
y
![](https://ids.lib.harvard.edu/ids/iiif/38979114/911,3054,46,46/full/0/native.jpg)
6