Publications

Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition

AuthID
P-00M-T33

Author(s)

Kasaei, SH

Tomé, AM

Lopes, LS

Editor(s)

Lee,DD;Sugiyama,M;Luxburg,UV;Guyon,I;Garnett,R

Document Type

Proceedings Paper

Year published

2016

Published

in ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 29 (NIPS 2016), ISSN: 1049-5258

Volume: 29, Pages: 1956-1964 (9)

Conference

30Th Annual Conference on Neural Information Processing Systems, Nips 2016, Date: 5 December 2016 through 10 December 2016, Sponsors: et al.;Google;Intel Corporation;KLA-Tencor;Microsoft;Winton

Indexing

Wos^®

Scopus^®

Metadata
Sources

Publication Identifiers

Scopus: 2-s2.0-85019182538

Wos: WOS:000458973704063

Source Identifiers

ISSN: 1049-5258

Export Publication Metadata

Marked List

Add to Marked List

Info

At this moment we don't have any links to full text documens.

Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition

Useful Links

Get Help

Federated Authentication (Click on the image)

Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition

Useful Links

Get Help