Employing Hierarchical Clustering and Reinforcement Learning for Attribute-Based Zero-Shot Classification

Name: Employing Hierarchical Clustering and Reinforcement Learning for Attribute-Based Zero-Shot Classification
Creator: Bin Liu
Published: 2019-05-15T14:33:59.224Z
Keywords: Machine Learning

Liu, Bin

doi:10.17632/r3v39665bm.1

Employing Hierarchical Clustering and Reinforcement Learning for Attribute-Based Zero-Shot Classification

Published: 15 May 2019| Version 1 | DOI: 10.17632/r3v39665bm.1

Contributor:

Bin Liu

Description

low-level features extracted from AwA and aPaY using vgg19 and googlenet and attribute annotations of labels; HCRL implemented on Weka; Configuration of the experiments in the corresponding article.

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The original image file is too large, please refer to the footnote cited in the article URL. Training data used 5% and 3% of the sample size respectively.

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National University of Defense Technology

Employing Hierarchical Clustering and Reinforcement Learning for Attribute-Based Zero-Shot Classification

Description

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