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Unsupervised auxiliary visual words discovery for large-scale image object retrieval
2011
CVPR 2011
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The AVWs are automatically discovered by feature propagation and selection in textual and visual image graphs in an unsupervised manner. ...
Meanwhile, the selection process can also notably reduce the number of features (to 1.4%) and can further facilitate indexing in large-scale image object retrieval. ...
., [4] ) to construct the large-scale image graph by MapReduce. To cluster images on the image graph, we apply affinity propagation (AP) [5] for graph-based clustering. ...
doi:10.1109/cvpr.2011.5995639
dblp:conf/cvpr/KuoLCYH11
fatcat:22isjgfpancspgtiigczwh2ip4
Affinity Propagation for Class Exemplar Mining
[chapter]
2010
Lecture Notes in Computer Science
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Firstly, we obtain an object specific cluster of graphs using a similarity propagation based graph clustering (SPGC) method. ...
The popular affinity propagation based clustering algorithm is then individually applied to each object specific cluster. ...
Similarity Propagation Based Graph Clustering(SPGC) In the text retrieval literature, a standard method for improving performance is query expansion. ...
doi:10.1007/978-3-642-14980-1_18
fatcat:lluxbbdkbvazpdfg6qjj3be4ou
Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement
2012
IEEE transactions on multimedia
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Index Terms-Image graph, image object retrieval, semantic feature discovery, tag refinement. Taiwan. ...
The proposed framework can be directly applied to various applications, such as keyword-based image search, image object retrieval, and tag refinement. ...
To cluster images on the image graph, we apply affinity propagation (AP) [28] for graph-based clustering. ...
doi:10.1109/tmm.2012.2190386
fatcat:midugvtgbfefzgmewb5soaesda
A Scalable Graph-Based Semi-Supervised Ranking System for Content-Based Image Retrieval
2013
International Journal of Multimedia Data Engineering and Management
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The authors propose a scalable graph-based semi-supervised ranking system for image retrieval. ...
An asymmetric relevance vector is created for each second layer graph by propagating initial scores from the first layer. ...
CONCLUSION AND FUTURE WORK We propose a novel scalable graph-based semi-supervised ranking system for image retrieval. ...
doi:10.4018/ijmdem.2013100102
fatcat:c4b76naaejhyhcwxghskmk7lte
Local similarity learning for pairwise constraint propagation
2014
Multimedia tools and applications
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Effective propagation algorithms have previously been designed based on the graph-based semi-supervised learning framework. ...
Pairwise constraint propagation studies the problem of propagating the scarce pairwise constraints across the entire dataset. ...
and the source are credited. ...
doi:10.1007/s11042-013-1796-y
fatcat:ydgaumee7vg6dei3tmcq3wb6vu
Regularized Diffusion Process on Bidirectional Context for Object Retrieval
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Consequently, RDP, ARDP and HRDP constitute a generic tool for object retrieval in most commonly-used settings, no matter the input relationships between objects are derived from the same domain or not ...
, and in pairwise formulation or not. ...
Xiang Bai by the National Program for Support of Top-notch Young Professionals and the Program for HUST Academic Frontier Youth Team, to Dr. ...
doi:10.1109/tpami.2018.2828815
pmid:29993682
fatcat:vtzomm3nvndypdonvkjxelgsby
Scalable Face Track Retrieval in Video Archives Using Bag-of-Faces Sparse Representation
2017
IEEE transactions on circuits and systems for video technology (Print)
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between performance and retrieval time. ...
Using the proposed method, a face track is encoded as a single bag-of-faces sparse representation and therefore allowing efficient indexing method to handle large-scale data. ...
Once the graph is constructed, finally, propagation algorithm is applied to compute the of people names for clusters by propagating name by cluster similarities from neighboring clusters. ...
doi:10.1109/tcsvt.2016.2538520
fatcat:kz5hizoemvc2vellnonmocc44i
Congruency-Based Reranking
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
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We present a tool for re-ranking the results of a specific query by considering the (n+1)×(n+1) matrix of pairwise similarities among the elements of the set of n retrieved results and the query itself ...
The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. ...
The prior probabilities of the l ij variables are derived from the pairwise handwriting-based image similarity of i and j, and are expressed by the pairwise models γ ij (l ij ). ...
doi:10.1109/cvpr.2014.270
dblp:conf/cvpr/Ben-ShalomLWDBSCHB14
fatcat:prmbvndp5fhblgacbpshebxnu4
Active Congruency-Based Reranking
2016
Frontiers in Digital Humanities
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We present a tool for re-ranking the results of a specific query by considering the matrix of pairwise similarities among the elements of the set of retrieved results and the query itself. ...
The tool is based on graphical Bayesian models, which reinforce retrieved items strongly linked to other retrievals, and on repeated clustering to measure the stability of the obtained associations. ...
The prior probabilities of the l ij variables are derived from the pairwise handwriting-based 130 image similarity of i and j, and are expressed by the pairwise models γ ij (l ij ). ...
doi:10.3389/fdigh.2016.00007
fatcat:imaybbxhhrf6hcl2gqqn7velee
Re-ranking by Multi-feature Fusion with Diffusion for Image Retrieval
2015
2015 IEEE Winter Conference on Applications of Computer Vision
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In addition, we utilize a probabilistic model based on the statistics of similarity scores of similar and dissimilar image pairs to determine the weight for each graph. ...
We present a re-ranking algorithm for image retrieval by fusing multi-feature information. We utilize pairwise similarity scores between images to exploit the underlying relationships among images. ...
For each feature, given the query and initially retrieved images, we construct an undirected graph whose vertices represent these images and in which edge strength is the pairwise similarity score between ...
doi:10.1109/wacv.2015.82
dblp:conf/wacv/YangMD15
fatcat:fk7gfojn5bg7to2rlhtxkm5dfm
Google based name search: Resolving mixed entities on the web
2009
2009 Fourth International Conference on Digital Information Management
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In particular, since the correct number of clusters is often unknown, we study a state-of-the-art unsupervised clustering solution based on propagation of pairwise similarities of entities. ...
For development of such a system, we propose a web service based interface, an unsupervised clustering scheme, and cluster ranking algorithms. ...
On et al. introduced multilevel graph partitioning scheme to address the scalable issue of name disambiguation problem on both bibliographic and information retrieval domains [10] . ...
doi:10.1109/icdim.2009.5356763
dblp:conf/icdim/OnL09
fatcat:62s2p4e7ebelpbzvjknnl5l3li
Author Index
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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Scenes Shape-based Similarity Retrieval of Doppler Images for Clinical Decision Support Türetken, Engin Delineating Trees in Noisy 2D Images and 3D Image-Stacks Turk, Matthew Workshop: Location-based ...
Affinities for Spectral Segmentation
Authority-Shift Clustering: Hierarchical Clustering by Authority Seeking on Graphs
Unsupervised Detection and Segmentation of Identical Objects
Nonparametric ...
doi:10.1109/cvpr.2010.5539913
fatcat:y6m5knstrzfyfin6jzusc42p54
Community Detection in Multiplex Networks
[article]
2021
arXiv
pre-print
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community structures and to what extent the evaluated methods are scalable. ...
We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. ...
Figure 16 reports on the results of pairwise analysis among Pillar Equal Partitioning and Semi-Pillar Non-equal Partitioning, with Omega index values for the pairwise similarities. ...
arXiv:1910.07646v3
fatcat:vxfxgpohurg4pf4tgr57cmljcm
Web-Scale Responsive Visual Search at Bing
[article]
2018
arXiv
pre-print
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The system accommodates tens of billions of images in the index, with thousands of features for each image, and can respond in less than 200 ms. ...
In order to overcome the challenges in relevance, latency, and scalability in such large scale of data, we employ a cascaded learning-to-rank framework based on various latest deep learning visual features ...
Image retrieval: The heavy lifting happens in the image retrieval module, which retrieves visually similar images based on the extracted features and intents. ...
arXiv:1802.04914v2
fatcat:unw36qpu7fdcjg46tnuvj4xtje
Spectral Clustering and Vantage Point Indexing for Efficient Data Retrieval
2018
International Journal of Electrical and Computer Engineering (IJECE)
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The technique clusters and indexes the densely populated high dimensional data points for effective data retrieval based on user query. ...
In order to overcome the limitation, Spectral Clustering Based VP Tree Indexing Technique is introduced. ...
Spectral Clustering is to form a pairwise similarity matrix "S", compute Laplacian matrix "L" and eigenvectors of "L". ...
doi:10.11591/ijece.v8i4.pp2261-2271
fatcat:tcallsen7fdknfd2ohqedjw4t4
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