Transfer deep convolutional activation-based features for domain adaptation in sensor networks

Transfer deep convolutional activation-based features for domain adaptation in sensor networks

Abstract In this paper, we propose a novel method named transfer deep convolutional activation-based features (TDCAF) for domain adaptation in sensor networks. Specifically, we first train a siamese network with weight sharing to map the images from different domains into the same feature space, whi...

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Bibliographic Details
Main Authors: Zhong Zhang, Donghong Li
Format: Article
Language:English
Published: SpringerOpen 2018-03-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Sensor networks
Domain adaptation
Deep convolutional activations
Vertical pooling
Online Access:http://link.springer.com/article/10.1186/s13638-018-1059-8

Internet

http://link.springer.com/article/10.1186/s13638-018-1059-8

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