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| 1 | Image retrieval based on multi-concept detector and semantic correlation显示文摘With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the single concept image retrieval, which has limited practical usability. In practice, users always employ an Internet image retrieval system with multi-concept queries, but, the related existing approaches are often ineffective because the only combination of single-concept query techniques is adopted. At present semantic concept based multi-concept image retrieval is becoming an urgent issue to be solved. In this paper, a novel Multi-Concept image Retrieval Model(MCRM) based on the multi-concept detector is proposed, which takes a multi-concept as a whole and directly learns each multi-concept from the rearranged multi-concept training set. After the corresponding retrieval algorithm is presented, and the log-likelihood function of predictions is maximized by the gradient descent approach. Besides, semantic correlations among single-concepts and multiconcepts are employed to improve the retrieval performance, in which the semantic correlation probability is estimated with three correlation measures, and the visual evidence is expressed by Bayes theorem, estimated by Support Vector Machine(SVM). Experimental results on Corel and IAPR data sets show that the approach outperforms the state-of-the-arts. Furthermore, the model is beneficial for multi-concept retrieval and difficult retrieval with few relevant images. | XU HaiJiao HUANG ChangQin PAN Peng ZHAO GanSen XU ChunYan LU YanSheng CHEN Deng WU JiYi | 2015 | Science China Chemistry2015，58，12： | 3 |
| 2 | Implementation of scalable power and area efficient high-throughput Viterbi decoders显示文摘 | Gemmeke T Gansen M Noll T G | 2002 | IEEE J Sol Sta Circ2002，37，7： | 1 |
| 3 | Rosacea-like demodicidosis associated with acguired imunodefici显示文摘 | Gansen T Kastner U Kreuter A | 2001 | Br J Dermatol2001，144，1： | 1 |
| 4 | Digital LAMP in a sample self-digitization(SD)chip显示文摘 | Gansen A Herrick A M Dimov I K | 2012 | Lab Chip2012，12，12： | 1 |
| 5 | Digital LAMP in a sample self - digitization ( SD ) chip 显示文摘 | Gansen A Herrick AM Dimov IK | 2012 | Labehip2012，12，2： | 1 |
| 6 | Single-photon detection using a quantum dot optically gated field-effect transistor with high internal quantum efficiency 显示文摘 | Rowe M A Gansen E J Greene M | 2006 | Applied Physics Letters2006，89，25： | 1 |
| 7 | Writeback throttling in a virtualized system with SCM显示文摘 | Dingding LI Xiaofei LIAO Hai JIN Yong TANG Gansen ZHAO | 2016 | Frontiers of Computer Science2016，10，1： | 1 |
| 8 | Operational Analysis of a Quantum Dot Optically Gated Field-Effect Transistor as a Single-Photon Detector显示文摘 | Gansen E J Rowe M A Greene M B Greene M B Rosenberg D Harvey T E Su M Y Hadfield R H Nam S W Mirin R P | 2007 | IEEE Journal of selected topics in quantum electronics2007，13，4： | 1 |
| 9 | Rosacea-like demodicidosis associated with acguired imunodefici 显示文摘 | Gansen T Kastner U Kreuter A | 2001 | Br J Dermatol2001，144，1： | 1 |
| 10 | Site - speeif ic integration of Agrobacterium T - DNA in Arabidopsis thaliana mediate by Cre recombinase 显示文摘 | VERGUNST A C GANSEN L E T HOOYKAAS P J J | 1998 | Nuel Acids Res1998，26，11： | 1 |
| 11 | Photon-number discrimination using a semiconductor quantum dot optically gated field-effect transistor显示文摘 | Gansen E J Rowe M A Greene M B | | 0，，05： | 1 |
| 12 | Transport properties of a quantum dot based optically gated field-effect transistor显示文摘 | Rowe M A Gansen E J Greene M | | 0，，25： | 1 |
| 13 | A Policy Integration Method Based on Multilevel Security for Data Integration显示文摘Integrating and sharing data from different data sources is one of the trends to make better use of data. However,data integration hampers data confidentiality where each data source has its own access control policy. This paper includes a discussion on the issue about access control across multiple data sources when they are combined together in the scenario of searching over these data. A method based on multilevel security for data integration is proposed. The proposed method allows the merging of policies and also tackles the issue of policy conflicts between different data sources. | WANG Xinming TAN Haoxiang CHEN Kaijun TANG Hua ZHAO Gansen TANG Yong NIE Ruihua | 2015 | Wuhan University Journal of Natural Sciences2015，20，6： | 0 |
| 14 | Editorial显示文摘With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the single concept image retrieval, which has limited practical usability. In practice, users always employ an Internet image retrieval system with multi-concept queries, but, the related existing approaches are often ineffective because the only combination of single-concept query techniques is adopted. At present semantic concept based multi-concept image retrieval is becoming an urgent issue to be solved. In this paper, a novel Multi-Concept image Retrieval Model(MCRM) based on the multi-concept detector is proposed, which takes a multi-concept as a whole and directly learns each multi-concept from the rearranged multi-concept training set. After the corresponding retrieval algorithm is presented, and the log-likelihood function of predictions is maximized by the gradient descent approach. Besides, semantic correlations among single-concepts and multiconcepts are employed to improve the retrieval performance, in which the semantic correlation probability is estimated with three correlation measures, and the visual evidence is expressed by Bayes theorem, estimated by Support Vector Machine(SVM). Experimental results on Corel and IAPR data sets show that the approach outperforms the state-of-the-arts. Furthermore, the model is beneficial for multi-concept retrieval and difficult retrieval with few relevant images. | XU HaiJiao HUANG ChangQin PAN Peng ZHAO GanSen XU ChunYan LU YanSheng CHEN Deng WU JiYi | 2015 | Science China(Physics,Mechanics & Astronomy)2015，58，12： | 0 |
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