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Learning with privileged information for photo aesthetic assessment
Yangyang SHU
, Qian LI
, Shaowu LIU
,
Guandong XU
Offices of the President (P)
Research output
:
Contribution to journal
›
Articles
›
peer-review
26
Citations (Scopus)
Overview
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Keyphrases
Learning Using Privileged Information
100%
Image Aesthetic Assessment
100%
Privileged Information
100%
Aesthetic Evaluation
33%
Deep Convolutional Neural Network (deep CNN)
33%
Copyright
16%
Assessment Task
16%
Student Performance
16%
Benchmark Dataset
16%
Aesthetic Quality
16%
Attribute Learning
16%
Pairwise Ranking
16%
Dependency Relations
16%
Training Stages
16%
Complex Network Structure
16%
Ranking Loss
16%
Machine Learning Tasks
16%
Probabilistic Dependencies
16%
Attribute Information
16%
Photo Aesthetics
16%
Computer Science
Deep Convolutional Neural Networks
100%
Assessment Task
50%
Machine Learning
50%
Experimental Result
50%
Network Structures
50%
Dependency Relation
50%
Complex Networks
50%
Related Attribute
50%
Attribute Information
50%
Aesthetic Quality
50%
Psychology
Neural Network
100%