NDLI: Active learning with label correlation exploration for multi-label image classification

Content Provider	IET Digital Library
Author	Wu, Jian Xing Ye, Chen Sheng, Victor S. Zhang, Jing Zhao, Pengpeng Cui, Zhiming
Abstract	Multi-label image classification has attracted considerable attention in machine learning recently. Active learning is widely used in multi-label learning because it can effectively reduce the human annotation workload required to construct high-performance classifiers. However, annotation by experts is costly, especially when the number of labels in a dataset is large. Inspired by the idea of semi-supervised learning, in this study, the authors propose a novel, semi-supervised multi-label active learning (SSMAL) method that combines automated annotation with human annotation to reduce the annotation workload associated with the active learning process. In SSMAL, they capture three aspects of potentially useful information – classification prediction information, label correlation information, and example spatial information – and they use this information to develop an effective strategy for automated annotation of selected unlabelled example-label pairs. The experimental results obtained in this study demonstrate the effectiveness of the authors' proposed approach.
Starting Page	577
Ending Page	584
Page Count	8
ISSN	17519632
Volume Number	11
e-ISSN	17519640
Issue Number	Issue 7, Oct (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/11/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0243
Journal	IET Computer Vision
Publisher Date	2017-07-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Annotation Classification Prediction Information Computer Vision And Image Processing Technique Example Spatial Information Human Annotation Image Capture Image Classification Image Recognition Knowledge Engineering Technique Label Correlation Exploration Label Correlation Information Learning in AI Machine Learning Multilabel Image Classification Semisupervised Multilabel Active Learning Method SSMAL Method
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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