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Unsupervised Computer
Vision
Stitch Fix, Styling Algorithms Research Talk
The Current State of the Art
TJ Torres
Data Scientist, Stitch Fix
WHY DEEP LEARNING?
Turns out NNs are great feature extractors.
Team name
Entry description
Classification
error
Localization
error
GoogLeNet
No localization. Top5 val score is 6.66% error.
0.06656
0.606257
VGG
a combination of multiple ConvNets, including a net trained on images of
different size (fusion weights learnt on the validation set); detected boxes
were not updated
0.07325
0.256167
VGG
a combination of multiple ConvNets, including a net trained on images of
different size (fusion done by averaging); detected boxes were not updated
0.07337
0.255431
VGG
a combination of multiple ConvNets (by averaging)
0.07405
0.253231
VGG
a combination of multiple ConvNets (fusion weights learnt on the validation
set)
0.07407
0.253501
Leaderboard
WHY DEEP LEARNING?
Turns out NNs are great feature extractors.
Team name
Entry description
Classification
error
Localization
error
GoogLeNet
No localization. Top5 val score is 6.66% error.
0.06656
0.606257
VGG
a combination of multiple ConvNets, including a net trained on images of
different size (fusion weights learnt on the validation set); detected boxes
were not updated
0.07325
0.256167
VGG
a combination of multiple ConvNets, including a net trained on images of
different size (fusion done by averaging); detected boxes were not updated
0.07337
0.255431
VGG
a combination of multiple ConvNets (by averaging)
0.07405
0.253231
VGG
a combination of multiple ConvNets (fusion weights learnt on the validation
set)
0.07407
0.253501
Leaderboard
Convolution: gives local, translation invariant feature hierarchy
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