Fusing generic objectness and deformable part-based models for weakly supervised object detection
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: 2014DOI: 10.1109/ICRA.2014.6907019
Keyword(s): data visualisation,n gradient methods,n learning (artificial intelligence),n rendering (computer graphics),n stochastic processes,n transfer functions,n DR methods,n DVR,n GCSE,n dictionary learning,n dimension reduction,n dimensionality reduction,n direct volume rendering,n geometry constrained sparse embedding,n geometry distance,n medical visualization,n multidimensional transfer function design,n real CT data sets,n stochastic gradient de
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Fusing generic objectness and deformable part-based models for weakly supervised object detection
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| contributor author | Tang, Yuxing | |
| contributor author | Wang, Xiaofang | |
| contributor author | Dellandrea, Emmanuel | |
| contributor author | Masnou, Simon | |
| contributor author | Chen, Liming | |
| date accessioned | 2020-03-12T22:50:29Z | |
| date available | 2020-03-12T22:50:29Z | |
| date issued | 2014 | |
| identifier other | 7025827.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1096406?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Fusing generic objectness and deformable part-based models for weakly supervised object detection | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8236920 | |
| subject keywords | data visualisation | |
| subject keywords | n gradient methods | |
| subject keywords | n learning (artificial intelligence) | |
| subject keywords | n rendering (computer graphics) | |
| subject keywords | n stochastic processes | |
| subject keywords | n transfer functions | |
| subject keywords | n DR methods | |
| subject keywords | n DVR | |
| subject keywords | n GCSE | |
| subject keywords | n dictionary learning | |
| subject keywords | n dimension reduction | |
| subject keywords | n dimensionality reduction | |
| subject keywords | n direct volume rendering | |
| subject keywords | n geometry constrained sparse embedding | |
| subject keywords | n geometry distance | |
| subject keywords | n medical visualization | |
| subject keywords | n multidimensional transfer function design | |
| subject keywords | n real CT data sets | |
| subject keywords | n stochastic gradient de | |
| identifier doi | 10.1109/ICRA.2014.6907019 | |
| journal title | mage Processing (ICIP), 2014 IEEE International Conference on | |
| filesize | 690234 | |
| citations | 0 |