Polysemious visual representation based on feature aggregation for large scale image applications
| LEADER | caa a22 4500 | ||
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| 001 | 605446741 | ||
| 003 | CHVBK | ||
| 005 | 20210128100128.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s11042-014-1975-5 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s11042-014-1975-5 | ||
| 245 | 0 | 0 | |a Polysemious visual representation based on feature aggregation for large scale image applications |h [Elektronische Daten] |c [Xinghang Song, Shuqiang Jiang, Shuhui Wang, Liang Li, Qingming Huang] |
| 520 | 3 | |a Multiple image features and multiple semantic concepts from the images have intrinsic and complex relations. These relations influence the effectiveness of image semantic analysis methods, especially on the large scale problems. In this paper, a framework of generating polysemious image representation through three levels of feature aggregation is proposed. In the codebook level aggregation, visual dictionaries are learned for each feature type, and each image feature can be reconstructed with this dictionary. In the semantic level aggregation, the multiple concept distributions are learned with each feature codebook by using the improved local anchor embedding. Then the polysemious representation for for single feature type can be established after this level. In the multiple feature level aggregation, final image polysemious representation is obtained through multiple feature fusion with a weighted pooling approach. Through the proposed framework, multiple feature fusion and multiple semantic descriptions are both achieved in an integrated way. Experimental evaluations on large scale image dataset validate the effectiveness of the proposed method. | |
| 540 | |a Springer Science+Business Media New York, 2014 | ||
| 690 | 7 | |a Polysemious representation |2 nationallicence | |
| 690 | 7 | |a Feature aggregation |2 nationallicence | |
| 690 | 7 | |a Max pooling |2 nationallicence | |
| 690 | 7 | |a Large scale |2 nationallicence | |
| 700 | 1 | |a Song |D Xinghang |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | |
| 700 | 1 | |a Jiang |D Shuqiang |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | |
| 700 | 1 | |a Wang |D Shuhui |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | |
| 700 | 1 | |a Li |D Liang |u University of Chinese Academy of Sciences, Beijing, China |4 aut | |
| 700 | 1 | |a Huang |D Qingming |u University of Chinese Academy of Sciences, Beijing, China |4 aut | |
| 773 | 0 | |t Multimedia Tools and Applications |d Springer US; http://www.springer-ny.com |g 74/2(2015-01-01), 595-611 |x 1380-7501 |q 74:2<595 |1 2015 |2 74 |o 11042 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s11042-014-1975-5 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s11042-014-1975-5 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Song |D Xinghang |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Jiang |D Shuqiang |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wang |D Shuhui |u Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology(ICT), No.6 Kexueyuan South Road Zhongguancun, Haidian District, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Li |D Liang |u University of Chinese Academy of Sciences, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Huang |D Qingming |u University of Chinese Academy of Sciences, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Multimedia Tools and Applications |d Springer US; http://www.springer-ny.com |g 74/2(2015-01-01), 595-611 |x 1380-7501 |q 74:2<595 |1 2015 |2 74 |o 11042 | ||