Generalized Zero Shot Learning via Synthesis Pseudo Features

Generalized Zero Shot Learning via Synthesis Pseudo Features

Compared with conventional zero-shot learning (ZSL), generalized ZSL (GZSL) is more challenging because the test instances may come from seen and unseen classes. The most existing GZSL methods learn a visual-semantic mapping function to bridge the knowledge transfer from seen to unseen classes by us...

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Bibliographic Details
Main Authors: Chuanlong Li, Xiufen Ye, Haibo Yang, Yatong Han, Xiang Li, Yunpeng Jia
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Generalized zero-shot learning
pseudo feature synthesis
image classification
supervised learning
multi-class classification
Online Access:https://ieeexplore.ieee.org/document/8746253/

Internet

https://ieeexplore.ieee.org/document/8746253/

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