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.
Files
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