Machine Generated Data
Tags
Amazon
created on 2019-04-02
Clarifai
created on 2018-04-18
old | 98.3 | |
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98.2 | ||
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vintage | 98.1 | |
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art | 97.4 | |
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ship | 94.1 | |
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retro | 93.1 | |
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watercraft | 92.6 | |
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painting | 92.5 | |
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no person | 91.7 | |
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antique | 90.9 | |
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illustration | 90.3 | |
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ancient | 87.5 | |
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transportation system | 84.6 | |
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architecture | 83.6 | |
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building | 82.6 | |
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water | 79.9 | |
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travel | 79.5 | |
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frigate | 75.9 | |
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lithograph | 75.8 | |
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sailboat | 74.8 | |
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Imagga
created on 2018-04-18
Google
created on 2018-04-18
sailing ship | 94 | |
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ship of the line | 87.5 | |
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fluyt | 79.2 | |
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watercraft | 76.2 | |
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ship | 76 | |
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galleon | 72.9 | |
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galiot | 72.1 | |
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east indiaman | 70.4 | |
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clipper | 67 | |
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caravel | 65.6 | |
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tree | 63.7 | |
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manila galleon | 62.3 | |
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galley | 60.3 | |
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brig | 59.5 | |
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brigantine | 58.4 | |
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first rate | 57.6 | |
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galeas | 56.8 | |
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barque | 54.6 | |
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visual arts | 53.7 | |
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art | 53.6 | |
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Color Analysis
Feature analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/9695046/91,109,4126,2650/full/0/native.jpg)
Painting | 97.8% | |
|
Categories
Imagga
streetview architecture | 63.4% | |
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beaches seaside | 29.4% | |
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paintings art | 3.7% | |
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nature landscape | 2.1% | |
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cars vehicles | 0.8% | |
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interior objects | 0.3% | |
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sunrises sunsets | 0.3% | |
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Captions
Microsoft
created on 2018-04-18
an old picture of a person | 43.1% | |
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a screenshot of a video game | 21.6% | |
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a close up of a statue | 21.5% | |
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Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3805,2624,207,108/full/0/native.jpg)
Regis
![](https://ids.lib.harvard.edu/ids/iiif/9695046/567,2666,191,98/full/0/native.jpg)
Bella
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3012,2624,226,124/full/0/native.jpg)
Ifrael
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3563,2627,232,114/full/0/native.jpg)
prinil,
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3423,2666,140,51/full/0/native.jpg)
cun
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3010,2624,1004,129/full/0/native.jpg)
Ifrael er. cun prinil, Regis
![](https://ids.lib.harvard.edu/ids/iiif/9695046/341,2682,204,86/full/0/native.jpg)
S.D.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/130,2704,98,57/full/0/native.jpg)
2.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/761,2662,334,130/full/0/native.jpg)
jn. et fe
![](https://ids.lib.harvard.edu/ids/iiif/9695046/315,2666,780,111/full/0/native.jpg)
S. D. Bella jn etfe.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/130,2665,966,132/full/0/native.jpg)
2. S. D. Bella jn etfe. s S.D. Bella jn. et fe
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3264,2659,140,86/full/0/native.jpg)
er.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/341,2688,73,67/full/0/native.jpg)
s
![](https://ids.lib.harvard.edu/ids/iiif/9695046/150,2639,3786,148/full/0/native.jpg)
ril Reg
2. S. D. Bella n. etfe
![](https://ids.lib.harvard.edu/ids/iiif/9695046/442,2685,102,102/full/0/native.jpg)
D.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/571,2685,167,102/full/0/native.jpg)
Bella
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3643,2639,109,82/full/0/native.jpg)
ril
![](https://ids.lib.harvard.edu/ids/iiif/9695046/3808,2639,127,82/full/0/native.jpg)
Reg
![](https://ids.lib.harvard.edu/ids/iiif/9695046/150,2685,82,102/full/0/native.jpg)
2.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/262,2685,166,102/full/0/native.jpg)
S.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/780,2685,102,102/full/0/native.jpg)
n.
![](https://ids.lib.harvard.edu/ids/iiif/9695046/895,2685,151,102/full/0/native.jpg)
etfe