Localized deep extreme learning machines for efficient RGB-D object recognition
Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks. The former lack representation ability while the latter require large amounts of training data and learning time. In real-time robotics applications involving RGB-D senso...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Electrical and Electronic Engineers, Inc. (IEEE)
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/64704/ http://irep.iium.edu.my/64704/ http://irep.iium.edu.my/64704/ http://irep.iium.edu.my/64704/7/64704%20Localized%20Deep%20Extreme%20Learning.pdf http://irep.iium.edu.my/64704/8/64704%20Localized%20Deep%20Extreme%20Learning%20SCOPUS.pdf |