AI Data for Miscellaneous: Training for general manufactures ?: (?) out ? | AI Explorer

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Human Generated Data

Title Miscellaneous: Training for general manufactures ?: (?) out ?	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, 3.2002.3353.2

Human Generated Data

Title

Miscellaneous: Training for general manufactures ?: (?) out ?

People

Artist: Unidentified Artist,

Date

c. 1903

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.3353.2

Machine Generated Data

Color Analysis

Face analysis

Amazon

Microsoft

Google

AWS Rekognition

Age	11-18
Gender	Male, 54.7%
Happy	45.2%
Disgusted	45.4%
Sad	45.5%
Confused	45.2%
Angry	45.2%
Surprised	45.2%
Calm	53.2%

Feature analysis

Amazon

Person

Tie

Person	99.1%

Captions

Microsoft
created on 2019-06-05

a group of people posing for a photo	96.5%

an old photo of a group of people posing for the camera	95.2%

an old photo of a group of people posing for a picture	95.1%

Text analysis

Amazon

bt

Google

bat

Human	99.1

Person	99.1

Person	99

Person	98.5

Person	98.1

Nature	98

Person	97.9

Person	97.4

Accessories	97

Accessory	97

Tie	97

Outdoors	96.4

Tie	95.1

Person	94.4

Person	94.1

Person	93.6

Person	93.4

Shack	93

Hut	93

Rural	93

Countryside	93

Building	93

Person	92

Apparel	90

Clothing	90

Person	81.5

Person	80.5

Dugout	78.6

People	76.8

Crowd	75.1

Person	66.5

Audience	58.6

Person	53.4

Person	51.9

people	99.9

group	99.4

many	99.4

group together	98.2

adult	96.8

man	95.7

administration	95.1

military	93.4

war	93.1

woman	91.4

child	91.1

leader	88.8

wear	86.1

several	86.1

music	84.9

portrait	84.7

crowd	83.9

retro	82.2

vehicle	77.9

facial expression	76.9

sketch	69.8

drawing	57.2

representation	42.8

art	23.2

old	20.9

grunge	18.7

design	15.2

religion	14.3

architecture	14.1

vintage	13.2

ancient	13

sculpture	12.9

decoration	12.4

statue	12.1

business	10.9

artistic	10.4

pattern	10.2

symbol	10.1

people	10

dirty	9.9

antique	9.8

history	9.8

modern	9.8

person	9.8

style	9.6

black	9.6

travel	9.1

city	9.1

technology	8.9

man	8.9

graphic	8.7

light	8.7

men	8.6

column	8.6

element	8.3

shape	8.1

music	8.1

detail	8

kin	8

scene	7.8

motion	7.7

historical	7.5

retro	7.4

figure	7.3

face	7.1

Photograph	97

Snapshot	87

Crew	73.3

Photography	62.4

Team	59.4

Monochrome	54.4

Family	53.7

person	99.6

clothing	97.4

posing	97.3

military uniform	96

group	95.6

old	94.3

drawing	90.8

man	87.3

human face	70.9

sketch	66.5

cartoon	58.8

painting	52.2

crowd	0.7

Age	19-36
Gender	Male, 53.1%
Disgusted	45.4%
Happy	45%
Surprised	45.1%
Angry	51.1%
Confused	45.1%
Calm	45.2%
Sad	48%

Age	20-38
Gender	Male, 54.1%
Disgusted	45.1%
Confused	45.7%
Angry	47.2%
Sad	45.5%
Surprised	45.4%
Happy	45%
Calm	51.1%

Age	26-44
Gender	Male, 54%
Surprised	45.3%
Happy	45.1%
Confused	45.4%
Sad	45.6%
Calm	47.1%
Disgusted	47.1%
Angry	49.4%

Age	23-38
Gender	Male, 53%
Surprised	45.3%
Disgusted	45.3%
Confused	45.4%
Sad	48.2%
Calm	49.8%
Happy	45.2%
Angry	45.7%

Age	26-43
Gender	Male, 54.9%
Sad	45.2%
Disgusted	45.1%
Surprised	45.2%
Happy	54%
Confused	45.2%
Angry	45.1%
Calm	45.2%

Age	45-63
Gender	Male, 54.9%
Disgusted	45.1%
Confused	45.1%
Happy	45.1%
Calm	54.3%
Surprised	45.1%
Sad	45.2%
Angry	45.1%

Age	16-27
Gender	Male, 54%
Surprised	45.3%
Calm	52.6%
Happy	45.2%
Sad	46.1%
Confused	45.5%
Angry	45.3%
Disgusted	45.1%

Age	26-43
Gender	Female, 51.5%
Calm	49.2%
Surprised	45.6%
Disgusted	48.3%
Confused	45.6%
Sad	45.4%
Happy	45.5%
Angry	45.4%

Age	29-45
Gender	Male, 54.7%
Calm	52.9%
Sad	45.6%
Confused	45.3%
Happy	45.3%
Angry	45.3%
Disgusted	45.3%
Surprised	45.4%

Age	26-43
Gender	Male, 54.5%
Calm	54.1%
Sad	45.1%
Confused	45.2%
Happy	45.1%
Angry	45.2%
Disgusted	45.1%
Surprised	45.2%

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

Surprise	Very unlikely
Anger	Very unlikely
Sorrow	Very unlikely
Joy	Very unlikely
Headwear	Very unlikely
Blurred	Very unlikely

paintings art	59.3%

interior objects	31.8%

streetview architecture	7.2%

text visuals	1.3%

Human Generated Data

Title

Miscellaneous: Training for general manufactures ?: (?) out ?

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, 3.2002.3353.2

Human Generated Data

Title

Miscellaneous: Training for general manufactures ?: (?) out ?

People

Artist: Unidentified Artist,

Date

c. 1903

Classification

Photographs

Credit Line

Harvard Art Museums/Fogg Museum, Transfer from the Carpenter Center for the Visual Arts, Social Museum Collection, 3.2002.3353.2

Machine Generated Data

Tags

Amazoncreated on 2019-06-05

Clarifaicreated on 2019-06-05

Imaggacreated on 2019-06-05

Googlecreated on 2019-06-05

Microsoftcreated on 2019-06-05

Color Analysis

Face analysis

Amazon

Microsoft

Google

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

AWS Rekognition

Microsoft Cognitive Services

Microsoft Cognitive Services

Microsoft Cognitive Services

Microsoft Cognitive Services

Microsoft Cognitive Services

Microsoft Cognitive Services

Google Vision

Google Vision

Google Vision

Google Vision

Feature analysis

Amazon

Categories

Imagga

Captions

Microsoftcreated on 2019-06-05

Text analysis

Amazon

Google

Amazon
created on 2019-06-05

Clarifai
created on 2019-06-05

Imagga
created on 2019-06-05

Google
created on 2019-06-05

Microsoft
created on 2019-06-05

Microsoft
created on 2019-06-05