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Improving image retrieval performance by inter-query learning with one-class support vector machines

Iker Gondra, DouglasR. Heisterkamp, Jing Peng
2004 Neural computing & applications (Print)  
Relevance feedback (RF) is an iterative process which improves the performance of content-based image retrieval by modifying the query and similarity metric based on the user's feedback on the retrieval  ...  We present a novel RF framework that learns one-class support vector machines (1SVM) from retrieval experience to represent the set memberships of users' high-level concepts and stores them in a "concept  ...  Recently, support vector machines (SVM) have been applied to CBIR systems with RF to significantly improve retrieval performance [3, 9, 19] .  ... 
doi:10.1007/s00521-004-0415-2 fatcat:52tpn57wgva2xa4nlc7q2qhqde

Using Biased Support Vector Machine to Improve Retrieval Result in Image Retrieval with Self-organizing Map [chapter]

Chi-Hang Chan, Irwin King
2004 Lecture Notes in Computer Science  
Moreover, we apply our Self-Organizing Mapbased inter-query technique to reorganize the feature vector space, in order to incorporate the information provided by past queries and improve the retrieval  ...  performance for future queries.  ...  Acknowledgement This work is supported in part by the RGC Research Grant Direct Allocation #2050259.  ... 
doi:10.1007/978-3-540-30499-9_109 fatcat:ty725i53kfgaznviqd6aw53uke

Improving the Initial Image Retrieval Set by Inter-Query Learning with One-Class SVMs [chapter]

Iker Gondra, Douglas R. Heisterkamp, Jing Peng
2003 Intelligent Systems Design and Applications  
In this paper, we focus on the possibility of incorporating prior experience (obtained from the historical interaction of users with the system) to improve the retrieval performance on future queries.  ...  We propose learning one-class SVMs from retrieval experience to represent the set memberships of users' query concepts.  ...  Recently, Support Vector Machines (SVM) have been applied to CBIR systems with relevance feedback to significantly improve retrieval performance [3] .  ... 
doi:10.1007/978-3-540-44999-7_38 fatcat:3o4qrzxv4zgo3mxlvuqdzyrw6e

A Similarity Learning Approach to Content-Based Image Retrieval: Application to Digital Mammography

I. El-Naqa, Y. Yang, N.P. Galatsanos, R.M. Nishikawa, M.N. Wernick
2004 IEEE Transactions on Medical Imaging  
effectively incorporated into this learning framework to achieve improvement in retrieval precision based on online interaction with users.  ...  Specifically, we explore the use of neural networks and support vector machines to predict the user's notion of similarity.  ...  machine-learning algorithms (neural networks and support vector machines) are trained to predict the measures of image similarity reported by human observers.  ... 
doi:10.1109/tmi.2004.834601 pmid:15493691 fatcat:rou34ywrabeerdr7mfkdo7vhpq

The Application of User Log for Online Business Environment using Content-Based Image Retrieval System

Kien-ping Chung, Sandy Chong, Chun Fung, Jia Li
2006 2006 IEEE International Conference on e-Business Engineering (ICEBE'06)  
Over the past few years, inter-query learning has gained much attention in the research and development of content-based image retrieval (CBIR) systems.  ...  This is largely due to the capability of inter-query approach to enable learning from the retrieval patterns of previous query sessions.  ...  Acknowledgement This project is supported by a grant awarded by the 2005 Murdoch University Research Excellence Grant Schemes (REGS).  ... 
doi:10.1109/icebe.2006.99 dblp:conf/icebe/ChungCFL06 fatcat:pbv4btqpjbbp5pnejrsyo37yyi

Summarizing inter-query learning in content-based image retrieval via incremental semantic clustering

I. Gondra, D.R. Heisterkamp
2004 International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.  
In previous work, we developed a novel Relevance Feedback (RF) framework that learns One-class Support Vector Machines (1SVM) from retrieval experience to represent the set memberships of users' high level  ...  By doing a fuzzy classification of a query into the regions of support represented by the 1SVMs, past experience is merged with short-term (i.e., intra-query) learning.  ...  In previous work [3] , we presented a novel RF framework that uses One-Class Support Vector Machines (1SVM) to model set membership knowledge about users' high level concepts.  ... 
doi:10.1109/itcc.2004.1286583 dblp:conf/itcc/GondraH04 fatcat:ygyjbqb4wrhd7db22tgqij5z6m

Medical Image Retrieval with Query-Dependent Feature Fusion Based on One-Class SVM

Yonggang Huang, Jun Zhang, Yongwang Zhao, Dianfu Ma
2010 2010 13th IEEE International Conference on Computational Science and Engineering  
In this paper, we present a novel query dependent feature fusion method for medical image retrieval based on one class support vector machine.  ...  image queries only based on multiply image samples provided by the user, and the learned feature fusion models can reflect the different importances of a special feature for different image queries.  ...  ACKNOWLEDGMENT This research work was supported by grants from the Chinese Special Project of Science and Technology: Core electronic devices, high-end general chips and infrastructural software (2010ZX01042  ... 
doi:10.1109/cse.2010.30 dblp:conf/cse/HuangZZM10 fatcat:x7kptxkuufaynblqxr4fd37gyi

Dynamic feature weights with relevance feedback in content-based image retrieval

Esin Guldogan, Moncef Gabbouj
2009 2009 24th International Symposium on Computer and Information Sciences  
The proposed method utilizes intracluster and inter-cluster information for representing the descriptive and discriminative properties of the features according to the labeled images by the user.  ...  In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights.  ...  12, Canny Edge Histogram, and Dominant Color with 3 colors. 50 queries are performed on the database by selecting five images randomly from each class.  ... 
doi:10.1109/iscis.2009.5291921 dblp:conf/iscis/GuldoganG09 fatcat:mbbpjbx7nvgexfwjr63uxdizh4

Semantics Discovery for Image Indexing [chapter]

Joo-Hwee Lim, Jesse S. Jin
2004 Lecture Notes in Computer Science  
Support vector machines (SVM) are first trained on local image blocks from a small number of images labeled as several semantic categories.  ...  The training samples for these DSRs are automatically induced from cluster memberships and subject to support vector machine learning to form local semantic detectors for DSRs.  ...  Now we can perform supervised learning again on X + i and X − i using say support vector machines S i (x) as DSR models.  ... 
doi:10.1007/978-3-540-24670-1_21 fatcat:nunyebsnwzeiphf4ywkfpii3ge

Markov Process Based Retrieval for Encrypted JPEG Images

Hang Cheng, Xinpeng Zhang, Jiang Yu, Fengyong Li
2015 2015 10th International Conference on Availability, Reliability and Security  
After that, with the multi-class support vector machine (SVM), the feature of the encrypted query image can be converted into a vector with low dimensionality determined by the number of image categories  ...  This paper develops a retrieval scheme for encrypted JPEG images based on a Markov process.  ...  and multi-class support vector machine (SVM).  ... 
doi:10.1109/ares.2015.18 dblp:conf/IEEEares/ChengZYL15 fatcat:mg4w6w6imjgajpgsnp5ojomvm4

Markov process-based retrieval for encrypted JPEG images

Hang Cheng, Xinpeng Zhang, Jiang Yu, Fengyong Li
2016 EURASIP Journal on Information Security  
After that, with the multi-class support vector machine (SVM), the feature of the encrypted query image can be converted into a vector with low dimensionality determined by the number of image categories  ...  This paper develops a retrieval scheme for encrypted JPEG images based on a Markov process.  ...  and multi-class support vector machine (SVM).  ... 
doi:10.1186/s13635-015-0028-6 fatcat:lp3p5c26trae3k2nf27fbx2t6a

Content based Feature Combination Method for Face Image Retrieval using Neural Network and SVM Classifier for Face Recognition

Ningthoujam Sunita Devi, K. Hemachandran
2017 Indian Journal of Science and Technology  
The query image is recognized from the faces returned by retrieval process by using Support Vector Machine (SVM).  ...  For the face image retrieval purpose, Artificial Neural Network (ANN) is adopted and its performance on the retrieval process is evaluated with PCA, WT, GW and their fusion as a feature vector.  ...  The recognition of query image is performed by using SVM based on the images returned by retrieval process.  ... 
doi:10.17485/ijst/2017/v10i24/111123 fatcat:zi2wx52igbe6boaqsgnvn5jc3y

An Ensemble Based Evolutionary Approach to the Class Imbalance Problem with Applications in CBIR

Aun Irtaza, Syed Adnan, Khawaja Ahmed, Arfan Jaffar, Ahmad Khan, Ali Javed, Muhammad Mahmood
2018 Applied Sciences  
A wide range of CBIR applications consider classification techniques, such as artificial neural networks (ANN), support vector machines (SVM), etc. to understand the query image content to retrieve relevant  ...  The experiments reveal that the proposed method outperforms various state-of-the-art methods and significantly improves the image retrieval performance.  ...  Aschraf et al. applied multi-class support vector machines (SVM) on the feature repository obtained by the Bandlet transform [8] .  ... 
doi:10.3390/app8040495 fatcat:diof4242dzaatmj5jf4b6i23e4

Learning and inferring a semantic space from user's relevance feedback for image retrieval

Xiaofei He, Wei-Ying Ma, Oliver King, Mingjing Li, Hongjiang Zhang
2002 Proceedings of the tenth ACM international conference on Multimedia - MULTIMEDIA '02  
the system will gradually improve its retrieval performance through accumulated user interactions.  ...  The proposed short-and long-term learning frameworks have been integrated into an image retrieval system.  ...  In this case, support vector machine learning algorithm can be used to learn the target function for retrieving target images.  ... 
doi:10.1145/641043.641080 fatcat:zsdqbxrqqbhdrccyrqj22nepyy

Learning and inferring a semantic space from user's relevance feedback for image retrieval

Xiaofei He, Wei-Ying Ma, Oliver King, Mingjing Li, Hongjiang Zhang
2002 Proceedings of the tenth ACM international conference on Multimedia - MULTIMEDIA '02  
the system will gradually improve its retrieval performance through accumulated user interactions.  ...  The proposed short-and long-term learning frameworks have been integrated into an image retrieval system.  ...  In this case, support vector machine learning algorithm can be used to learn the target function for retrieving target images.  ... 
doi:10.1145/641007.641080 dblp:conf/mm/HeMKLZ02 fatcat:basoxn3c2zfthbhzxh54vw75um
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