Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition
Recognizing semantic category of objects and scenes captured using vision-based sensors is a challenging yet essential capability for mobile robots and UAVs to perform high-level tasks such as long-term autonomous navigation. However, extracting discriminative features from multi-modal inputs, such...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Elsevier
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/61281/ http://irep.iium.edu.my/61281/ http://irep.iium.edu.my/61281/ http://irep.iium.edu.my/61281/1/Learning%20a%20deeply%20supervised%20multi-modal%20RGB-D%20embedding%20for%20semantic%20scene%20and%20object%20category%20recognition.pdf http://irep.iium.edu.my/61281/7/61281-Learning%20a%20deeply%20supervised%20multi-modal-SCOPUS.pdf |
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http://irep.iium.edu.my/61281/http://irep.iium.edu.my/61281/
http://irep.iium.edu.my/61281/
http://irep.iium.edu.my/61281/1/Learning%20a%20deeply%20supervised%20multi-modal%20RGB-D%20embedding%20for%20semantic%20scene%20and%20object%20category%20recognition.pdf
http://irep.iium.edu.my/61281/7/61281-Learning%20a%20deeply%20supervised%20multi-modal-SCOPUS.pdf