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Editorial for the ICMR 2018 special issue
2019
International Journal of Multimedia Information Retrieval
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In "Multi-view Collective Tensor Decomposition for Cross-modal Hashing", Cui et al. address the problem of cross-media retrieval with hash codes learned with a tensor model. ...
Experiments show that the multi-view collective tensor decomposition performs well against several existing cross-modal hashing approaches on two commonly used datasets. ...
doi:10.1007/s13735-019-00168-9
fatcat:irnfud2fszbq7mx25pno73b2sm
Table of contents
2019
IEEE Transactions on Image Processing
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Sun 2665 Collective Reconstructive Embeddings for Cross-Modal Hashing ............................................................. .................................................................. ...
Restoration and Enhancement Weighted Tensor Rank-1 Decomposition for Nonlocal Image Denoising ..................... Y. Wu, L. Fang, and S. ...
doi:10.1109/tip.2019.2905937
fatcat:hdjjnnguk5dera2si44df5zude
Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry and Fusion
[article]
2020
arXiv
pre-print
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With the development of web technology, multi-modal or multi-view data has surged as a major stream for big data, where each modal/view encodes individual property of data objects. ...
Throughout this survey, we further indicate that the critical components for this field go to collaboration, adversarial competition and fusion over multi-modal spaces. ...
It jointly learned unified hash codes for cross-modal instances and a pair of hash functions for queries. Cao et al. ...
arXiv:2006.08159v1
fatcat:g4467zmutndglmy35n3eyfwxku
Multi-modal Deep Analysis for Multimedia
2019
IEEE transactions on circuits and systems for video technology (Print)
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2019 pre-print arXiv:1910.04964v1 fatcat:76yma7ca4fhajduyuyuos3csziOther Versions
hashing. ...
In this article, we present a deep and comprehensive overview for multi-modal analysis in multimedia. ...
ACKNOWLEDGMENT We thank Guohao Li, Shengze Yu and Yitian Yuan for providing relevant materials and valuable opinions. This work will never be accomplished without their useful suggestions. ...
doi:10.1109/tcsvt.2019.2940647
fatcat:l4tchrkgrnaeradvc4nhfan2w4
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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., +, TIP 2020 4254-4268
Multi-Task Consistency-Preserving Adversarial Hashing for Cross-Modal
Retrieval. ...
.,
+, TIP 2020 225-236
Collective Affinity Learning for Partial Cross-Modal Hashing. Guo, J., +,
TIP 2020 1344-1355
Context-Aware Graph Label Propagation Network for Saliency Detection. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Preparation of Papers for IEEE ACCESS
2020
IEEE Access
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INDEX TERMS Cybersecurity, malware, multi-modal data, network diffusion, unsupervised machine learning, multi-view data. 77436 VOLUME 8, 2020 ...
In doing so, we propose a new algorithm, Cross-Modal Influence Clustering, for characterizing malware samples into threat actor groups. ...
The final consistent graph output is clustered via spectral clustering for the final clusters. • ETL-MSC: Essential Tensor Learning for Multi-view Spectral Clustering [23] uses a regularized tensor decomposition ...
doi:10.1109/access.2020.2989689
fatcat:jfzlwwsiqzgsfblvj4zkxoo3li
The heterogeneous feature selection with structural sparsity for multimedia annotation and hashing: a survey
2012
International Journal of Multimedia Information Retrieval
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Therefore, the selection of limited discriminative features for certain semantics is hence crucial to make the understanding of multimedia more interpretable. ...
This paper introduces many of the recent efforts in sparsitybased heterogenous feature selection, the representation of the intrinsic latent structure embedded in multimedia, and the related hashing index ...
For example, all of the heterogenous features from different views can be unified as a consensus representation for the cross-media semantics, and factorized into a latent spaces with a structured sparsity ...
doi:10.1007/s13735-012-0001-9
fatcat:4ihorofn6zbg3mzqnifihgcydm
Hetero-Manifold Regularisation for Cross-Modal Hashing
2018
IEEE Transactions on Pattern Analysis and Machine Intelligence
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To address both challenges, in this paper, we propose a novel method termed hetero-manifold regularisation (HMR) to supervise the learning of hash functions for efficient cross-modal search. ...
Recently, cross-modal search has attracted considerable attention but remains a very challenging task because of the integration complexity and heterogeneity of the multi-modal data. ...
for cross-modal hashing. ...
doi:10.1109/tpami.2016.2645565
pmid:28055849
fatcat:qayqzp3yyvcf7ayv4f6tgfwlsu
Table of contents
2020
IEEE Transactions on Image Processing
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Netto 1329 Collective Affinity Learning for Partial Cross-Modal Hashing ......................................... J. Guo and W. ...
Zhang 3612 Multi-Task Consistency-Preserving Adversarial Hashing for Cross-Modal Retrieval ....................................... ...................................................................... ...
doi:10.1109/tip.2019.2940372
fatcat:h23ul2rqazbstcho46uv3lunku
State of the journal
2019
International Journal of Multimedia Information Retrieval
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You are the core of the community and this journal. 4 ) 4 ICMR A special issue on the best papers from the ACM Multi-view Collective Tensor Decomposition for Cross-modal Hashing" by Limeng Cui, Jiawei ...
These factors motivated our major starting goals: create a high quality archival journal for the field of multimedia retrieval and aim for an average time to the first decision of roughly 1 month. ...
doi:10.1007/s13735-019-00184-9
fatcat:w47hoyk62je4llpvtalu6n6a7a
2021 Index IEEE Transactions on Knowledge and Data Engineering Vol. 33
2022
IEEE Transactions on Knowledge and Data Engineering
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The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TKDE Nov. 2021 3507-3519 Exploiting Subspace Relation in Semantic Labels for Cross-Modal Hashing. Shen, H.T., +, TKDE Oct. 2021 3351-3365 Joint Deep Multi-View Learning for Image Clustering. ...
., +, TKDE May 2021 1919-1933 Exploiting Subspace Relation in Semantic Labels for Cross-Modal Hashing. ...
doi:10.1109/tkde.2021.3128365
fatcat:4m5kefreyrbhpb3lhzvgqzm3qu
General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization
2022
Digital Threats: Research and Practice
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Non-negative tensor factorization, on the other hand, is a powerful unsupervised machine learning method that naturally models multi-dimensional data, capturing complex and multi-faceted details of behavior ...
Distinguishing malicious anomalous activities from unusual but benign activities is a fundamental challenge for cyber defenders. ...
We also thank Neale Pickett for providing helpful feedback on the IP address hashing schemes, and Austin Thresher for the feedback on our software design. ...
doi:10.1145/3519602
fatcat:uxt4l4g4pzayjhvxqmmgfksfpy
2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32
2021
IEEE Transactions on Knowledge and Data Engineering
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Yan, Y., +, TKDE Feb. 2020 288-301 Fast Discrete Collaborative Multi-Modal Hashing for Large-Scale Multimedia Retrieval. ...
Tang, J., +, TKDE May 2020 855-867 Fast Discrete Collaborative Multi-Modal Hashing for Large-Scale Multimedia Retrieval. ...
doi:10.1109/tkde.2020.3038549
fatcat:75f5fmdrpjcwrasjylewyivtmu
Supervised Fractional-order Embedding Geometrical Multi-view CCA (SFGMCCA) for Multiple Feature Integration
2020
IEEE Access
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INDEX TERMS Feature integration, multi-view, canonical correlation analysis, fractional-order technique, geometrical structure. 114340 This work is licensed under a Creative Commons Attribution 4.0 License ...
Multiset canonical correlation analysis (MCCA), which maximizes the sum of pairwise correlations of inter-view (i.e., between different features), is one of the powerful methods for integrating different ...
Recently, cross-modal retrieval has attracted attention. Specifically, hashing methods have gained increasing interests in facilitating large-scale cross-view retrieval tasks [56] , [57] . ...
doi:10.1109/access.2020.3003619
fatcat:nyina3vjbrb35lqs6y3a6ts3jm
2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30
2020
IEEE transactions on circuits and systems for video technology (Print)
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Lai, H., +, TCSVT April 2020 1162-1172 SCRATCH: A Scalable Discrete Matrix Factorization Hashing Framework for Cross-Modal Retrieval. ...
.,
+, TCSVT Oct. 2020 3788-3802
SCRATCH: A Scalable Discrete Matrix Factorization Hashing Framework
for Cross-Modal Retrieval. ...
A Memory-Efficient Hardware Architecture for Connected Component Labeling in Embedded System. ...
doi:10.1109/tcsvt.2020.3043861
fatcat:s6z4wzp45vfflphgfcxh6x7npu
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