Learning mid-level features from object hierarchy for image classification
| date accessioned | 2020-03-12T19:52:14Z | |
| date available | 2020-03-12T19:52:14Z | |
| date issued | 2014 | |
| identifier other | 6836095.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/993216?locale-attribute=en&show=full | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Learning mid-level features from object hierarchy for image classification | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8112415 | |
| subject keywords | Accuracy | |
| subject keywords | Computers | |
| subject keywords | Face | |
| subject keywords | Face detection | |
| subject keywords | Feature extraction | |
| subject keywords | Image color analysis | |
| subject keywords | Skin | |
| subject keywords | AdaBoost | |
| subject keywords | Gaussian pyramid | |
| subject keywords | face detection | |
| subject keywords | skin color feature | |
| identifier doi | 10.1109/MFI.2014.6997663 | |
| journal title | pplications of Computer Vision (WACV), 2014 IEEE Winter Conference on | |
| filesize | 1408116 | |
| citations | 0 | |
| contributor rawauthor | Albaradei, S. , Yang Wang , Liangliang Cao , Li-Jia Li |
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