Label-Embedding for Image Classification

Attributes act as intermediate representations that enable parameter sharing between classes, a must when training data is scarce. We propose to view attribute-based image classification as a label-embedding problem: each class is embedded in the space of attribute vectors. We introduce a function t...

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Vydáno v:	IEEE transactions on pattern analysis and machine intelligence Ročník 38; číslo 7; s. 1425 - 1438
Hlavní autoři:	Akata, Zeynep, Perronnin, Florent, Harchaoui, Zaid, Schmid, Cordelia
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.07.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Témata:	Animals Attributes Computer Science Computer vision Computer Vision and Pattern Recognition Encoding Fine Grained Image Classification Image classification Label Embedding Linear programming Loss measurement Subspace Learning Taxonomy Training attributes label embedding zero-shot learning Image classification Image Classification Attributes Label Embedding Zero-Shot Learning
ISSN:	0162-8828, 2160-9292, 1939-3539
On-line přístup:	Získat plný text
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