A Deep Multiview Active Learning for Large-Scale Image Classification
Joint Authors
Gu, Yuhong
Yao, Tuozhong
Wang, Wenfeng
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-15
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Multiview active learning (MAL) is a technique which can achieve a large decrease in the size of the version space than traditional active learning and has great potential applications in large-scale data analysis.
In this paper, we present a new deep multiview active learning (DMAL) framework which is the first to combine multiview active learning and deep learning for annotation effort reduction.
In this framework, our approach advances the existing active learning methods in two aspects.
First, we incorporate two different deep convolutional neural networks into active learning which uses multiview complementary information to improve the feature learnings.
Second, through the properly designed framework, the feature representation and the classifier can be simultaneously updated with progressively annotated informative samples.
The experiments with two challenging image datasets demonstrate that our proposed DMAL algorithm can achieve promising results than several state-of-the-art active learning algorithms.
American Psychological Association (APA)
Yao, Tuozhong& Wang, Wenfeng& Gu, Yuhong. 2020. A Deep Multiview Active Learning for Large-Scale Image Classification. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1197017
Modern Language Association (MLA)
Yao, Tuozhong…[et al.]. A Deep Multiview Active Learning for Large-Scale Image Classification. Mathematical Problems in Engineering No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1197017
American Medical Association (AMA)
Yao, Tuozhong& Wang, Wenfeng& Gu, Yuhong. A Deep Multiview Active Learning for Large-Scale Image Classification. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1197017
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197017