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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Steps to reproduce

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.

Institutions

National University of Defense Technology

Categories

Machine Learning

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