SAL-Net: Self-Supervised Attribute Learning for Object Recognition and Segmentation

Existing attribute learning methods rely on predefined attributes, which require manual annotations. Due to the limitation of human experience, the predefined attributes are not capable enough of providing enough description. This paper proposes a self-supervised attribute learning (SAL) method, whi...

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Veröffentlicht in:	Wireless communications and mobile computing Jg. 2021; H. 1
Hauptverfasser:	Yang, Shu, JingWang, Arif, Sheeraz, Jia, Minli, Zhong, Shunan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Hindawi 2021 John Wiley & Sons, Inc
Schlagworte:	Algorithms Annotations Classification Datasets Dictionaries Image annotation Image classification Image segmentation Learning Neural networks Object recognition Semantic segmentation Semantics
ISSN:	1530-8669, 1530-8677
Online-Zugang:	Volltext
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