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User Driven Systems To Bridge The Semantic Gap

Divna Djordjevic, Ebroul Izquierdo, Marcin Grzegorzek
2007 Zenodo  
Publication in the conference proceedings of EUSIPCO, Poznan, Poland, 2007  ...  ACK kernels, in multi feature space.  ...  Similarly, in [11] Bayesian inference is used on block based local image features for relevance feedback learning.  ... 
doi:10.5281/zenodo.40350 fatcat:hzpkiwsqa5enbkeihwi535wpya

Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval

Irwin E. Alber, Morton S. Farber, Nancy Yeager, Ziyou Xiong, William M. Pottenger, Belur V. Dasarathy
2001 Data Mining and Knowledge Discovery: Theory, Tools, and Technology III  
An interactive search and analysis tool is presented and tested based on a relevance feedback approach that uses the "human-in-the-loop" to enhance a content-based image retrieval process to rapidly find  ...  This paper demonstrates the capability of a set of image search algorithms and display tools to search large databases for multi-and hyperspectral image cubes most closely matching a particular query cube  ...  The relevance feedback methodology uses the "human-in-the-loop" to aid in the process of retrieving hard-to-define multi-spectral image objects.  ... 
doi:10.1117/12.421092 dblp:conf/dmkdttt/AlberFYXP01 fatcat:qc4otm6asbanngap4zspmqg3dq

Evaluating multimodal relevance feedback techniques for medical image retrieval

Dimitrios Markonis, Roger Schaer, Henning Müller
2015 Information retrieval (Boston)  
Results using the ImageCLEF 2012 benchmark database for medical image retrieval show the potential of relevance feedback techniques in medical image retrieval.  ...  Relevance feedback is a powerful tool in information retrieval. This study evaluates relevance feedback techniques with regard to the content they use.  ...  Acknowledgements This work was supported by the EU 7th Framework Program in the context of the Khresmoi project (grant 257528).  ... 
doi:10.1007/s10791-015-9260-4 fatcat:fbp7rtqpt5euvpptl4q2xyqihq

A Multi-instance Multi-label Learning Framework of Image Retrieval [chapter]

Chaojun Wang, Zhixin Li, Canlong Zhang
2014 IFIP Advances in Information and Communication Technology  
A multi-instance and multi-label learning method based on Content Based Image Retrieve ( CBIR) is proposed in this paper, and the image processing stage we use in image retrieval process is multi-instance  ...  According to the user to select an image to generate positive sample packs and anti-packages, using multi-instance learning algorithms to learn, using the image retrieval and relevance feedback, the experimental  ...  For the above all kinds of methods for initial retrieval and related feedback average retrieval time are shown in table1.  ... 
doi:10.1007/978-3-662-44980-6_27 fatcat:mfjtjv7rnjd35msuwm4hmcqcpm

Image Hunter at ImageCLEF 2012 Personal Photo Retrieval Task

Roberto Tronci, Luca Piras, Gabriele Murgia, Giorgio Giacinto
2012 Conference and Labs of the Evaluation Forum  
For this challenge we used Image Hunter, a content based image retrieval tool with relevance feedback previously developed by ourselves.  ...  This is a pilot task that aims to provide a test bed for QBE-based retrieval scenarios in the scope of personal information retrieval based on a collection of 5,555 personal images plus rich meta-data.  ...  The SVM is very handy for this kind of task because, in the case of image retrieval, we deal with high dimensional feature spaces and two "classes" (i.e. relevant and not-relevant).  ... 
dblp:conf/clef/TronciPMG12 fatcat:6lgjlii6obc7lgyqfcjspiunpa

Content based Image Processing using Relevance Feedback with Null Space LDA (NLDA)

C. Rajivegandhi, V. Murugesh
2012 International Journal of Computer Applications  
Relevance feedback is a technique for incorporating semantic information in image retrieval.  ...  It is better for the relevance feedback based on the user involvement in image retrieval system. By using the help of user's feedback, the resultant high-level semantic will be obtained.  ...  The relevance feedback process occurs in the following steps [4] . 1. Acquire the low-level feature vector for the query image. 2.  ... 
doi:10.5120/9692-4133 fatcat:p5cxj7mypfe6ddcnvvyv7jfozu

Towards Effective Relevance Feedback Methods in Content-Based Image Retrieval Systems

Sunitha Mostefai
2014 International Journal of Innovation Management and Technology  
In this paper we discuss the current state-of-the-art in Relevance Feedback as seen from content-based image retrieval point of view and recommend a novel approach for the future.  ...  To improve the retrieval (text, image, etc.,) performance in content-based image retrieval system, an approach was introduced, named "Relevance Feedback".  ...  Content-Based Image Retrieval with Relevance Feedback has been popular method for image retrieval [11] so, efficient index methodology is needed.  ... 
doi:10.7763/ijimt.2014.v5.482 fatcat:peldufn2tndhlcwjakvw6l2jlu

Promising Large Scale Image Retrieval by Using Intelligent Semantic Binary Code Generation Technique

Anuja khodaskar, Siddarth Ladhake
2015 Procedia Computer Science  
Experimental result clearly shows that performance of image retrieval is improved in term of accuracy, efficiency and retrieval time.  ...  Million images on internet is big challenge for accurate and efficient image retrieval as per user requirement.  ...  Relevance feedback After retrieving set relevant images, automatic or manual feedback is given to set of retrieved images. Relevance feedback improves accuracy of image retrieval.  ... 
doi:10.1016/j.procs.2015.04.183 fatcat:qq54n37jkjacdjm7w7tncaprju

Human-centric approaches to image understanding and retrieval

Rui Li, Preethi Vaidyanathan, Sai Mulpuru, Jeff Pelz, Pengcheng Shi, Cara Calvelli, Anne Haake
2010 2010 Western New York Image Processing Workshop  
A key goal of recent researches on image retrieval is to develop retrieval systems that respond to individual user's query for real time applications.  ...  This paper reports on the recent trends in Content Based Image Retrieval approaches and their resolved issues.  ...  Let ç be the set of relevant r images in the database and ç is the set of top retrieved t images for a query image.  ... 
doi:10.1109/wnyipw.2010.5649743 fatcat:tej3mc24ffgppa7aop4ea5qmku

Multi-Modal Interactive Approach to ImageCLEF 2007 Photographic and Medical Retrieval Tasks by CINDI

Md. Mahmudur Rahman, Bipin C. Desai, Prabir Bhattacharya
2007 Conference and Labs of the Evaluation Forum  
We experiment with multi-modal (e.g., image and text) interaction and fusion approaches based on relevance feedback information for image retrieval tasks of photographic and medical image collections.  ...  For a text-based image search, keywords from the annotated files are extracted and indexed by employing the vector space model of information retrieval.  ...  (i) = 0 if image in the rank position i is not relevant based on user's feedback and Rank(i) = (K − i)/(K − 1) for the relevant images.  ... 
dblp:conf/clef/RahmanDB07a fatcat:dapux3ruhrhgxi5zsbhoeacmgi

Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval

K.A. Hua, Ning Yu, Danzhou Liu
2006 22nd International Conference on Data Engineering (ICDE'06)  
in the feature space.  ...  In this paper we consider a new image retrieval paradigm -the Query Decomposition modelthat facilitates retrieval of semantically similar images from multiple neighborhoods in the feature space.  ...  The new method is capable of retrieving images with similar semantics but very different visual characteristics, i.e., relevant images that are scattered in the feature space. 2.  ... 
doi:10.1109/icde.2006.123 dblp:conf/icde/HuaYL06 fatcat:diglwbmfobd55l43q76mmi73ai


Mohd Suffian Sulaiman, Sharifalillah Nordin, Nursuriati Jamil
2017 Journal of Information and Communication Technology  
Ontology is a semantic technology that provides the possible approach to bridge the issue on semantic gap in image retrieval between low-level visual features and high-level human semantic.  ...  In this paper, an ontology has been utilized to reduce the semantic gap by developing a multi-modality ontology image retrieval with the enhancement of a retrieval mechanism by using the object properties  ...  Log-based Relevance Feedback The log-based relevance feedback incorporated the log data of users' relevance feedback with regular relevance feedback for image retrieval (Hoi, Lyu, & Jin, 2006) .  ... 
doi:10.32890/jict2017.16.1.8215 fatcat:7kfodi36xrdxznfgpjvtb3md2a

Content-based image retrieval using optimal feature combination and relevance feedback

Lijun Zhao, Jiakui Tang
2010 2010 International Conference on Computer Application and System Modeling (ICCASM 2010)  
In order to narrow the gap between user query concept and low-level features in CBIR, a multi-round relevance feedback (RF) strategy based on both support vector machine (SVM) and feature similarity is  ...  The experiment results showed that this SVM and feature similarity based relevance feedback using best feature combination can greatly improve the retrieval precision with the number off eedback increasing  ...  For the latter retrieval way, three rounds of relevance feedback are performed for each query image.  ... 
doi:10.1109/iccasm.2010.5620791 fatcat:wffoe3vq2jdrhjdza2tzu3ma4u

Multiple Layar Kernel-Based Approach in Relevance Feedback Content-Based Image Retrieval System

Kien-Ping Chung, Chun-Che Fung
2005 2005 International Conference on Machine Learning and Cybernetics  
Relevance feedback has drawn intense interest from many researchers in the field of content-based image retrieval (CBIR).  ...  In recent years, kernel-based approach has been a popular choice for the implementation of the relevance feedback based CBIR system.  ...  Conclusion A new multi-layer kernel based framework for the relevance feedback content-based image retrieval system has been introduced in this paper.  ... 
doi:10.1109/icmlc.2005.1526981 fatcat:ynf32iddkfdrzoqvmmgjgm6ow4

Opponent Color And Curvelet Transform Based Image Retrieval System Using Genetic Algorithm

Yesubai Rubavathi Charles, Ravi Ramraj
2015 Zenodo  
To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user's preference images.  ...  The recent scenario in the issues of image retrieval is to reduce the semantic gap between user's preference and low level features.  ...  CONCLUSION In this paper, we have introduced a semantic image retrieval system which incorporates genetic algorithm and relevance feedback for associating with low level features.  ... 
doi:10.5281/zenodo.1110855 fatcat:brbdlrlpwvbftenhvblwsjqery
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