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Mixed image-keyword query adaptive hashing over multilabel images

Xianglong Liu, Yadong Mu, Bo Lang, Shih-Fu Chang
2014 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
This article defines a new hashing task motivated by real-world applications in content-based image retrieval, that is, effective data indexing and retrieval given mixed query (query image together with  ...  Mixed image-keyword query adaptive hashing over multilabel images.  ...  An efficient query-adaptive bit selection method, integrated into this framework for both database and unseen label retrieval, enhances both the adaptivity and the scalability of the work.  ... 
doi:10.1145/2540990 fatcat:vhbxtrjo5zh5fbrdtd4fzai2ru

Scalable mining of small visual objects

Pierre Letessier, Olivier Buisson, Alexis Joly
2012 Proceedings of the 20th ACM international conference on Multimedia - MM '12  
This allows for an evaluation of any hashing scheme effectiveness in a more generalized way, and a comparison with other priors, e.g. guided by visual saliency concerns.  ...  The idea is that the collision frequencies obtained with hashing-based methods can actually be converted into a prior probability density function given as input to a weighted adaptive sampling algorithm  ...  Standardized vectors ∆q,m are then hashed with L ′ distinct LSH functions, each composed of k ′ random projections of the form: h ′ (∆) = a.∆ + b w (14) The slight modification that we introduce over this  ... 
doi:10.1145/2393347.2393431 dblp:conf/mm/LetessierBJ12 fatcat:b7uxyxmivzflpa4botxcpl2jyq

Deep learning of binary hash codes for fast image retrieval

Kevin Lin, Huei-Fang Yang, Jen-Hao Hsiao, Chu-Song Chen
2015 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Approximate nearest neighbor search is an efficient strategy for large-scale image retrieval.  ...  Encouraged by the recent advances in convolutional neural networks (CNNs), we propose an effective deep learning framework to generate binary hash codes for fast image retrieval.  ...  Our method is with the following characteristics: • We introduce a simple yet effective supervised learning framework for rapid image retrieval. • With small modifications to the network model, our deep  ... 
doi:10.1109/cvprw.2015.7301269 dblp:conf/cvpr/LinYHC15 fatcat:ldzjg37xlvg3tchpjfvvdpdhvm

Large-Scale Video Search with Efficient Temporal Voting Structure [article]

Ersin Esen, Savas Ozkan, Ilkay Atil
2016 arXiv   pre-print
Each of the representation is converted into hash code with Hamming Embedding method for further queries.  ...  In this work, we propose a fast content-based video querying system for large-scale video search. The proposed system is distinguished from similar works with two major contributions.  ...  EE feature is very fast to extract and requires very small storage, and hash code increases the scalability for both search and storage.  ... 
arXiv:1607.07160v1 fatcat:cnt2f52dinfe3hzhqdq55j3m5i

Densified Winner Take All (WTA) Hashing for Sparse Datasets

Beidi Chen, Anshumali Shrivastava
2018 Conference on Uncertainty in Artificial Intelligence  
Our experiments show that Densified WTA Hashing outperforms Vanilla WTA Hashing both in image retrieval and classification tasks consistently and significantly.  ...  In this paper, we identify a subtle issue with WTA, which grows with the sparsity of the datasets. This issue limits the discriminative power of WTA.  ...  It is widely known that hashing time is the major bottleneck, both in theory and practice, for the task of image retrieval.  ... 
dblp:conf/uai/ChenS18 fatcat:cd7zn36bzfgyjjhkwrj56ivcpi

Recent Advance in Content-based Image Retrieval: A Literature Survey [article]

Wengang Zhou, Houqiang Li, Qi Tian
2017 arXiv   pre-print
Numerous techniques have been developed for content-based image retrieval in the last decade.  ...  With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content.  ...  indexing structure for scalable image retrieval.  ... 
arXiv:1706.06064v2 fatcat:m52xwsw5pzfzdbxo5o6dye2gde

Table of Contents

2021 IEEE transactions on multimedia  
Jiang Complementary Incremental Hashing With Query-Adaptive Re-Ranking for Image Retrieval . . . . . . . . . . . . . . . . . . . . . . ...Factorized Tensor Dictionary Learning for Visual Tensor Data Completion  ...  Huang Multimedia Search and Retrieval Online Hashing With Bit Selection for Image Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Z. Weng and Y.  ... 
doi:10.1109/tmm.2021.3132246 fatcat:el7u2udtybddrpbl5gxkvfricy

Hierarchical semantic indexing for large scale image retrieval

Jia Deng, Alexander C. Berg, Li Fei-Fei
2011 CVPR 2011  
This paper addresses the problem of similar image retrieval, especially in the setting of large-scale datasets with millions to billions of images.  ...  An additional contribution is a novel hashing scheme (for bilinear similarity on vectors of probabilities, optionally taking into account hierarchy) that is able to reduce the computational cost of retrieval  ...  It may be possible to adapt some of those strategies to take into account variable similarities for hierarchical structure, but would require modification of the techniques, and would not necessarily improve  ... 
doi:10.1109/cvpr.2011.5995516 dblp:conf/cvpr/DengBL11 fatcat:muycjsyngfawrgei2al7vy3ydm

2021 Index IEEE Transactions on Multimedia Vol. 23

2021 IEEE transactions on multimedia  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  H Hamming distance Complementary Incremental Hashing With Query-Adaptive Re-Ranking for Image Retrieval.  ...  ., +, TMM 2021 4351-4362 Adaptation models Adaptive Partial Multi-View Hashing for Efficient Social Image Retrieval.  ... 
doi:10.1109/tmm.2022.3141947 fatcat:lil2nf3vd5ehbfgtslulu7y3lq

An Adaptive Image-based Plagiarism Detection Approach

Norman Meuschke, Christopher Gondek, Daniel Seebacher, Corinna Breitinger, Daniel Keim, Bela Gipp
2018 Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries - JCDL '18  
The proposed detection approach integrates established image analysis methods, such as perceptual hashing, with newly developed similarity assessments for images, such as ratio hashing and position-aware  ...  We propose an adaptive, scalable, and extensible image-based plagiarism detection approach suitable for analyzing a wide range of image similarities that we observed in academic documents.  ...  As shown in Table 2 , the true source images were retrieved at the top rank for all input images with a score above 0.5.  ... 
doi:10.1145/3197026.3197042 dblp:conf/jcdl/MeuschkeGSBKG18 fatcat:uesb4oemsjdrre5kyn7q5sle6u

Factorization Of Overlapping Harmonic Sounds Using Approximate Matching Pursuit

Steven K. Tjoa, K. J. Ray Liu
2011 Zenodo  
Yu et al. use LSH and order statistics to store chroma features in a hash table for audio content retrieval [28] .  ...  Because of its simplicity, robustness, and low complexity, LSH has become popular for solving many high-level problems beyond MIR such as search and retrieval of text and images.  ... 
doi:10.5281/zenodo.1414961 fatcat:knd3zfxl7jdy3nfidcyzq5iwli


Dr. Hanan Ahmed Al-Jubouri, Lecturer, Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq.
2019 Journal of Engineering and Sustainable Development  
However, searching for similar and relevant images from large-scale databases still poses a challenge for Content-Based Image Retrieval systems due to the gap between high-level meaning and low-level visual  ...  Whether it is for scientific research, medical or social networking, there is a growing demand for effective retrieval of digital images based on their visual content (e.g. colour and texture).  ...  Sara at el. [23] developed a retrieval system based on region using a joint scalable Bayesian segmentation for texture images.  ... 
doi:10.31272/jeasd.23.3.4 fatcat:ez6ilw4tsze2pl3ctzywthpalq

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

Jamil Ahmad, Muhammad Sajjad, Irfan Mehmood, Sung Wook Baik, Gayle E. Woloschak
2017 PLoS ONE  
Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares  ...  Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections.  ...  Acknowledgments The authors thank courtesy of TM Deserno, Dep. of Medical Informatics, RWTH Aachen, Germany, for providing IRMA dataset.  ... 
doi:10.1371/journal.pone.0181707 pmid:28771497 pmcid:PMC5542646 fatcat:vseqnumxhncafpz2gmpneb6opi

A Survey on Content Based Image Retrieval Using Convolutional Neural Networks

2020 International Journal of Advanced Trends in Computer Science and Engineering  
Traditional hashing techniques are most commonly used to provide high quality search results for labeled images.  ...  It also focuses on content based image retrieval technique (CBIR), with an unsupervised learning method using convolutional Neural Networks (CNN).  ...  However, scalable deep hashing [36] has been adapted for large-scale data learning and retrieval process.  ... 
doi:10.30534/ijatcse/2020/70952020 fatcat:vjpq2j2pdza5di426baglhavai

Dynamicity and Durability in Scalable Visual Instance Search [article]

Herwig Lejsek, Björn ór Jónsson, Laurent Amsaleg, Fririk Heiar Ásmundsson
2019 arXiv   pre-print
This article addresses the issue of dynamicity and durability for scalable indexing of very large and rapidly growing collections of local features for instance retrieval.  ...  Systems designed for visual instance search face the major challenge of scalability: a collection of a few million images used for instance search typically creates a few billion features that must be  ...  As a result, Sparse coding [65] , Fisher vectors [51] , and VLAD [26] were successfully applied to image classification and retrieval, but are too coarse-grained for instance retrieval.  ... 
arXiv:1805.10942v2 fatcat:hdapj4544vhxxory4bvnxx5pzq
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