Machine Generated Data
Tags
Amazon
created on 2019-04-05
Clarifai
created on 2018-03-22
Imagga
created on 2018-03-22
war | 34.3 | |
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weapon | 30.7 | |
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armament | 29.6 | |
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military | 29 | |
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cannon | 27.9 | |
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artillery | 25.6 | |
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vehicle | 24.5 | |
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gun | 24.2 | |
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tank | 23.7 | |
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weaponry | 22.6 | |
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high-angle gun | 20.2 | |
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bazooka | 19 | |
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sky | 16.6 | |
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army | 16.6 | |
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danger | 16.4 | |
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launcher | 16.2 | |
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military vehicle | 15.8 | |
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soldier | 15.6 | |
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gunnery | 14.9 | |
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aircraft | 14.7 | |
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uniform | 14.6 | |
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old | 13.9 | |
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camouflage | 13.7 | |
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conveyance | 13.6 | |
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protection | 13.6 | |
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transportation | 13.4 | |
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power | 13.4 | |
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plane | 12.6 | |
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vintage | 12.4 | |
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man | 12.1 | |
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tracked vehicle | 11.9 | |
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warfare | 11.8 | |
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propeller | 11.8 | |
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destruction | 11.7 | |
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conflict | 11.7 | |
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airplane | 11.6 | |
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armored vehicle | 11.4 | |
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male | 11.3 | |
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battle | 10.8 | |
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history | 10.7 | |
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rifle | 10.6 | |
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smoke | 10.2 | |
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black | 10.2 | |
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safety | 10.1 | |
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air | 10.1 | |
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clothing | 10.1 | |
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transport | 10 | |
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missile | 9.9 | |
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force | 9.8 | |
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fight | 9.7 | |
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clouds | 9.3 | |
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industrial | 9.1 | |
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field artillery | 9 | |
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landscape | 8.9 | |
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device | 8.7 | |
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industry | 8.5 | |
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travel | 8.4 | |
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stretcher | 8.4 | |
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city | 8.3 | |
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historic | 8.3 | |
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machine | 8.2 | |
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to | 8 | |
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person | 7.9 | |
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attack | 7.8 | |
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nuclear | 7.8 | |
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steam | 7.8 | |
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summer | 7.7 | |
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engine | 7.7 | |
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mask | 7.7 | |
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mechanism | 7.6 | |
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outdoors | 7.5 | |
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wheeled vehicle | 7.2 | |
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Google
created on 2018-03-22
airplane | 90.2 | |
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aviation | 89.8 | |
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aircraft | 87.2 | |
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air force | 84.8 | |
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black and white | 81.8 | |
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aerospace engineering | 79.7 | |
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military aircraft | 62.1 | |
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monochrome photography | 56.4 | |
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monochrome | 56.4 | |
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military | 55.8 | |
|
Color Analysis
Face analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/16084289/483,80,66,70/full/0/native.jpg)
AWS Rekognition
Age | 35-52 |
Gender | Male, 99.8% |
Disgusted | 2.3% |
Angry | 22.3% |
Sad | 10.2% |
Confused | 8.9% |
Calm | 36.5% |
Surprised | 11.6% |
Happy | 8.1% |
Feature analysis
Categories
Imagga
paintings art | 59.3% | |
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nature landscape | 36.8% | |
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cars vehicles | 2.2% | |
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pets animals | 0.8% | |
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streetview architecture | 0.6% | |
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beaches seaside | 0.3% | |
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food drinks | 0.1% | |
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Captions
Microsoft
created on 2018-03-22
a vintage photo of an old airplane | 88.2% | |
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a vintage photo of a plane | 87.5% | |
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a vintage photo of a man in a military uniform | 87.4% | |
|
Text analysis
Amazon
![](https://ids.lib.harvard.edu/ids/iiif/16084289/109,682,27,15/full/0/native.jpg)
Air
![](https://ids.lib.harvard.edu/ids/iiif/16084289/17,701,27,13/full/0/native.jpg)
he
![](https://ids.lib.harvard.edu/ids/iiif/16084289/230,699,82,15/full/0/native.jpg)
Sidewinda
![](https://ids.lib.harvard.edu/ids/iiif/16084289/196,680,54,18/full/0/native.jpg)
Com ba?
![](https://ids.lib.harvard.edu/ids/iiif/16084289/203,702,19,13/full/0/native.jpg)
a
![](https://ids.lib.harvard.edu/ids/iiif/16084289/915,672,70,20/full/0/native.jpg)
Mohees
![](https://ids.lib.harvard.edu/ids/iiif/16084289/258,680,58,18/full/0/native.jpg)
Couter:
![](https://ids.lib.harvard.edu/ids/iiif/16084289/121,703,33,11/full/0/native.jpg)
ata
![](https://ids.lib.harvard.edu/ids/iiif/16084289/137,681,54,18/full/0/native.jpg)
Ground
![](https://ids.lib.harvard.edu/ids/iiif/16084289/11,673,453,33/full/0/native.jpg)
Maverie Cope Air Ground a Sidewinda musoi (AIM-9L)
![](https://ids.lib.harvard.edu/ids/iiif/16084289/440,678,25,15/full/0/native.jpg)
CA
![](https://ids.lib.harvard.edu/ids/iiif/16084289/50,701,62,15/full/0/native.jpg)
Hamni:
![](https://ids.lib.harvard.edu/ids/iiif/16084289/17,697,178,23/full/0/native.jpg)
he Hamni: ata acluing
![](https://ids.lib.harvard.edu/ids/iiif/16084289/879,676,26,11/full/0/native.jpg)
b
![](https://ids.lib.harvard.edu/ids/iiif/16084289/320,680,54,18/full/0/native.jpg)
Mojavt
![](https://ids.lib.harvard.edu/ids/iiif/16084289/11,684,55,15/full/0/native.jpg)
Maverie
![](https://ids.lib.harvard.edu/ids/iiif/16084289/469,677,44,16/full/0/native.jpg)
/969
![](https://ids.lib.harvard.edu/ids/iiif/16084289/579,301,46,18/full/0/native.jpg)
AB637
![](https://ids.lib.harvard.edu/ids/iiif/16084289/372,694,93,25/full/0/native.jpg)
(AIM-9L)
![](https://ids.lib.harvard.edu/ids/iiif/16084289/195,680,317,20/full/0/native.jpg)
Com ba? Couter: Mojavt Oeoeit, Oeve T CA /969
![](https://ids.lib.harvard.edu/ids/iiif/16084289/67,682,38,20/full/0/native.jpg)
Cope
![](https://ids.lib.harvard.edu/ids/iiif/16084289/852,672,133,20/full/0/native.jpg)
Aabe b Mohees
![](https://ids.lib.harvard.edu/ids/iiif/16084289/383,681,31,13/full/0/native.jpg)
Oeve
![](https://ids.lib.harvard.edu/ids/iiif/16084289/321,700,46,13/full/0/native.jpg)
musoi
![](https://ids.lib.harvard.edu/ids/iiif/16084289/381,678,53,19/full/0/native.jpg)
Oeoeit,
![](https://ids.lib.harvard.edu/ids/iiif/16084289/146,700,49,22/full/0/native.jpg)
acluing
![](https://ids.lib.harvard.edu/ids/iiif/16084289/853,675,54,15/full/0/native.jpg)
Aabe
![](https://ids.lib.harvard.edu/ids/iiif/16084289/570,300,53,18/full/0/native.jpg)
A AB637
![](https://ids.lib.harvard.edu/ids/iiif/16084289/413,680,21,15/full/0/native.jpg)
T
![](https://ids.lib.harvard.edu/ids/iiif/16084289/570,302,15,16/full/0/native.jpg)
A
![](https://ids.lib.harvard.edu/ids/iiif/16084289/110,303,764,415/full/0/native.jpg)
AAB637
sk
: ara
![](https://ids.lib.harvard.edu/ids/iiif/16084289/574,308,48,20/full/0/native.jpg)
AAB637
![](https://ids.lib.harvard.edu/ids/iiif/16084289/860,303,14,16/full/0/native.jpg)
sk
![](https://ids.lib.harvard.edu/ids/iiif/16084289/110,708,7,10/full/0/native.jpg)
:
![](https://ids.lib.harvard.edu/ids/iiif/16084289/122,704,33,14/full/0/native.jpg)
ara