Human Generated Data

Title

Industrial Problems, Welfare Work: United States. Ohio. Dayton. National Cash Register Company: Welfare Institutions of the National Cash Register Company, Dayton, Ohio.: Features Educational to Employes: A Party Leaving Dayton for a Trip to other Cities

Date

c. 1903

People

Artist: Unidentified Artist,

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.3519.A.1

Human Generated Data

Title

Industrial Problems, Welfare Work: United States. Ohio. Dayton. National Cash Register Company: Welfare Institutions of the National Cash Register Company, Dayton, Ohio.: Features Educational to Employes: A Party Leaving Dayton for a Trip to other Cities

People

Artist: Unidentified Artist,

Date

c. 1903

Classification

Photographs

Machine Generated Data

Tags

Amazon
created on 2019-06-05

Human 99.6
Person 99.6
Person 99.4
Person 99.3
Person 99.2
Railway 98.9
Train Track 98.9
Rail 98.9
Transportation 98.9
Person 98.9
Person 98.5
Person 98.3
Person 97.6
Person 97.3
Vehicle 94.2
Train 94.2
Person 92.9
Person 89.3
Person 86.4
Passenger Car 79
Crowd 78.8
Person 73.7
People 69.4
Apparel 62.9
Clothing 62.9
Person 49.8
Person 42.6

Clarifai
created on 2019-06-05

people 99.8
many 99.3
group together 99
group 98.5
military 98
adult 97.7
railway 97.1
vehicle 95.9
administration 95.8
train 95.7
war 95.5
transportation system 94.4
man 93.8
uniform 92.2
leader 91.2
soldier 90.1
wear 90.1
police 89.5
woman 86.6
offense 85.9

Imagga
created on 2019-06-05

passenger car 93.2
car 83.9
wheeled vehicle 66.2
vehicle 49.7
train 36.3
station 33.1
building 32.9
architecture 29.8
travel 29.6
conveyance 29.3
city 24.1
transportation 23.3
urban 19.2
old 18.1
railroad 16.7
transport 16.4
journey 15.1
structure 15
window 14.8
subway 13.8
railway station 13.3
terminal 13.2
historical 13.2
railway 12.7
interior 12.4
track 11.7
history 11.6
passenger 11.6
hall 11.2
speed 11
landmark 10.8
traditional 10.8
tourism 10.7
subway train 10.4
wagon 10.2
exterior 10.1
house 10.1
historic 10.1
metro 9.9
rail 9.8
engine 9.6
roof 9.5
ancient 9.5
center 9.4
freight car 9.2
street 9.2
people 8.9
commuter 8.9
locomotive 8.8
facility 8.7
move 8.6
column 8.5
place 8.4
wall 8.1
night 8
public transport 7.9
door 7.7
motion 7.7
construction 7.7
buildings 7.6
floor 7.4
business 7.3
tourist 7.2
metal 7.2
sky 7

Google
created on 2019-06-05

Transport 93.3
Standing 80.9
History 72.6
Rolling stock 61.3
Vehicle 60.3
Team 59.4
Barracks 52

Microsoft
created on 2019-06-05

outdoor 99.3
train 96.9
person 93.4
black 77.6
group 75
vehicle 74.5
clothing 69
white 68.7
old 53.6

Face analysis

Amazon

AWS Rekognition

Age 45-63
Gender Male, 54.9%
Confused 45.4%
Sad 45.6%
Angry 45.5%
Calm 53.2%
Happy 45.1%
Disgusted 45.1%
Surprised 45.1%

AWS Rekognition

Age 26-44
Gender Male, 54.8%
Surprised 45.1%
Disgusted 45.4%
Sad 45.6%
Calm 53.5%
Happy 45.1%
Confused 45.1%
Angry 45.2%

AWS Rekognition

Age 35-52
Gender Male, 50.4%
Angry 45.1%
Disgusted 45.3%
Sad 45.1%
Surprised 45%
Happy 45%
Calm 54.4%
Confused 45%

AWS Rekognition

Age 35-52
Gender Male, 51.3%
Angry 45.2%
Surprised 45.4%
Sad 45.6%
Disgusted 45.2%
Confused 45.3%
Happy 45.2%
Calm 53.1%

AWS Rekognition

Age 20-38
Gender Male, 54.6%
Angry 45.2%
Sad 46.1%
Disgusted 45.1%
Happy 45.1%
Confused 45.3%
Calm 53.1%
Surprised 45.1%

AWS Rekognition

Age 35-52
Gender Female, 50.1%
Angry 46.7%
Disgusted 45.6%
Sad 46.5%
Calm 49.9%
Happy 45.2%
Surprised 45.7%
Confused 45.4%

AWS Rekognition

Age 35-52
Gender Male, 52.2%
Confused 45.5%
Calm 50.6%
Angry 45.8%
Surprised 45.4%
Sad 47%
Happy 45.1%
Disgusted 45.6%

AWS Rekognition

Age 26-43
Gender Male, 51.4%
Calm 51%
Happy 45.2%
Angry 45.6%
Disgusted 47%
Surprised 45.4%
Confused 45.3%
Sad 45.5%

AWS Rekognition

Age 27-44
Gender Male, 54%
Confused 45.7%
Disgusted 46.1%
Sad 45.8%
Surprised 45.4%
Calm 51.2%
Angry 45.7%
Happy 45.2%

AWS Rekognition

Age 45-63
Gender Female, 51.8%
Disgusted 45.1%
Sad 45.2%
Calm 54%
Confused 45.1%
Happy 45%
Surprised 45.3%
Angry 45.2%

AWS Rekognition

Age 38-59
Gender Male, 53.7%
Disgusted 45.4%
Confused 45.2%
Calm 46.1%
Angry 45.2%
Happy 45.1%
Sad 52.9%
Surprised 45.1%

AWS Rekognition

Age 27-44
Gender Male, 52.3%
Disgusted 46.2%
Surprised 45.4%
Happy 45.4%
Calm 51%
Angry 45.9%
Confused 45.3%
Sad 45.8%

AWS Rekognition

Age 20-38
Gender Male, 54%
Sad 45.8%
Happy 45.1%
Angry 45.8%
Calm 51.8%
Surprised 45.9%
Confused 45.4%
Disgusted 45.2%

AWS Rekognition

Age 57-77
Gender Female, 50.3%
Surprised 45.3%
Sad 45.3%
Calm 53.2%
Happy 45.2%
Disgusted 45.4%
Confused 45.2%
Angry 45.4%

Feature analysis

Amazon

Person 99.6%
Train 94.2%

Captions

Microsoft

a group of people standing in front of a train 95.9%
a group of people standing next to a train 95.8%
a group of people sitting at a train station 93.1%

Text analysis

Google

ansmm
ansmm