Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval
Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is to capture the high level semantic of user. The researchers of multimedia domain are trying to fix this issue with the help of Relevance Fee...
Uložené v:
| Vydané v: | Computers, materials & continua Ročník 70; číslo 1; s. 963 - 979 |
|---|---|
| Hlavní autori: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Henderson
Tech Science Press
01.01.2022
|
| Predmet: | |
| ISSN: | 1546-2226, 1546-2218, 1546-2226 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is to capture the high level semantic of user. The researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback (RF). However existing RF based approaches needs a number of iteration to fulfill user's requirements. This paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the system. In previous research work it is reported that SVM based RF approach generating better results for CBIR. Therefore, this paper focused on SVM based RF approach. To enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) before applying SVM on user feedback. The main objective of using these meta-heuristic was to increase the positive image sample size from SVM. Firstly steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO, finally SVM is applied using the positive sample generated through GA. The proposed technique is named as Particle Swarm Optimization Genetic Algorithm- Support Vector Machine Relevance Feedback (PSO-G A-SVM-RF). Precisions, recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 images. From experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches. |
|---|---|
| AbstractList | Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is to capture the high level semantic of user. The researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback (RF). However existing RF based approaches needs a number of iteration to fulfill user's requirements. This paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the system. In previous research work it is reported that SVM based RF approach generating better results for CBIR. Therefore, this paper focused on SVM based RF approach. To enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) before applying SVM on user feedback. The main objective of using these meta-heuristic was to increase the positive image sample size from SVM. Firstly steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO, finally SVM is applied using the positive sample generated through GA. The proposed technique is named as Particle Swarm Optimization Genetic Algorithm- Support Vector Machine Relevance Feedback (PSO-G A-SVM-RF). Precisions, recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 images. From experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches. |
| Author | Irtaza, Aun Dhahri, Habib Afzaal Abbasi, Aaqif Imran, Muhammad Jamal Malik, Arif Abbas, Qammar Mohammed Asem Othman, Esam Mahmood, Awais |
| Author_xml | – sequence: 1 givenname: Awais surname: Mahmood fullname: Mahmood, Awais – sequence: 2 givenname: Muhammad surname: Imran fullname: Imran, Muhammad – sequence: 3 givenname: Aun surname: Irtaza fullname: Irtaza, Aun – sequence: 4 givenname: Qammar surname: Abbas fullname: Abbas, Qammar – sequence: 5 givenname: Habib surname: Dhahri fullname: Dhahri, Habib – sequence: 6 givenname: Esam surname: Mohammed Asem Othman fullname: Mohammed Asem Othman, Esam – sequence: 7 givenname: Arif surname: Jamal Malik fullname: Jamal Malik, Arif – sequence: 8 givenname: Aaqif surname: Afzaal Abbasi fullname: Afzaal Abbasi, Aaqif |
| BookMark | eNp1kMtrAjEQxkOxULW99xjoeW1eG83Rii8QCn2cQ8zO6trdjU2i4H_fWHsohZ5mhvm-efx6qNO6FhC6p2TAmSTi0TZ2wAhjA0IVU_QKdWkuZMYYk51f-Q3qhbAjhEuuSBe9Lk5rXxV4enT1IVauNf6Ex_XG-SpuG_xkAhT4BWo4mtYCngEUa2M_8Hi_987YLS6dx8vGbCCpoq-Srr5F16WpA9z9xD56n03fJots9TxfTsarzHLKY2aAKyEoMGILKoaFYZaLUqgcrASgwlrGh-dCKWJ4IcVIFYqljlnnI05L3kcPl7nplM8DhKh37uDbtFInIjmTuaCjpCIXlfUuBA-l3vuqSW9qSvQ3Op3Q6TM6fUGXLPKPxVbRnOlEb6r6f-MXsip1HQ |
| CitedBy_id | crossref_primary_10_1016_j_displa_2024_102899 |
| Cites_doi | 10.3390/jtaer16030032 10.1016/j.ins.2020.08.040 10.1007/978-981-15-4474-3_7 10.1109/TIP.2005.863969 10.1016/j.proeng.2013.02.063 10.1016/j.ins.2016.09.021 10.1109/TPAMI.2006.134 10.1145/1348246.1348248 10.1023/A:1016568309421 10.1016/j.swevo.2018.01.011 10.1109/76.927422 10.1109/TSMCA.2002.802812 10.21833/ijaas.2016.12.007 10.1504/IJSISE.2012.046742 10.1186/s13673-019-0191-8 10.1109/76.927424 10.1007/s11042-020-08953-z 10.1016/j.ijepes.2010.03.001 10.1109/TKDE.2007.1003 10.1145/1126004.1126005 10.1016/j.eswa.2011.08.086 10.1109/TMM.2017.2711263 10.1109/TCSVT.2007.890634 10.1109/TSMCB.2006.880137 10.1145/2954930 10.1016/0165-0114(95)00256-1 10.1016/j.patcog.2011.03.016 10.1109/34.895972 10.1016/j.amc.2006.12.066 10.1109/TMM.2010.2046269 10.1109/TII.2019.2906083 10.1109/TFUZZ.2015.2417895 10.1007/s10766-016-0469-7 10.1109/34.955109 10.1007/s00500-016-2102-5 10.1109/ACCESS.2019.2959325 |
| ContentType | Journal Article |
| Copyright | 2022. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2022. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | AAYXX CITATION 7SC 7SR 8BQ 8FD ABUWG AFKRA AZQEC BENPR CCPQU DWQXO JG9 JQ2 L7M L~C L~D PHGZM PHGZT PIMPY PKEHL PQEST PQQKQ PQUKI PRINS |
| DOI | 10.32604/cmc.2022.019291 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Engineered Materials Abstracts METADEX Technology Research Database ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials - QC ProQuest Central ProQuest One ProQuest Central Korea Materials Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Proquest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China |
| DatabaseTitle | CrossRef Publicly Available Content Database Materials Research Database Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest One Academic Eastern Edition ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest Central China METADEX Computer and Information Systems Abstracts Professional ProQuest Central Engineered Materials Abstracts ProQuest One Academic UKI Edition ProQuest Central Korea ProQuest Central (New) ProQuest One Academic Advanced Technologies Database with Aerospace ProQuest One Academic (New) |
| DatabaseTitleList | Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1546-2226 |
| EndPage | 979 |
| ExternalDocumentID | 10_32604_cmc_2022_019291 |
| GroupedDBID | AAFWJ AAYXX ACIWK ADMLS AFFHD AFKRA ALMA_UNASSIGNED_HOLDINGS BENPR CCPQU CITATION EBS EJD J9A OK1 P2P PHGZM PHGZT PIMPY RTS TUS 7SC 7SR 8BQ 8FD ABUWG AZQEC DWQXO JG9 JQ2 L7M L~C L~D PKEHL PQEST PQQKQ PQUKI PRINS |
| ID | FETCH-LOGICAL-c313t-ae39441e20cd147da2c34f495ec6ee14cc2375ec6990a3d6489d92ee1ab5831f3 |
| IEDL.DBID | PIMPY |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000696956000014&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1546-2226 1546-2218 |
| IngestDate | Sun Nov 09 08:29:06 EST 2025 Sat Nov 29 03:13:19 EST 2025 Tue Nov 18 22:15:20 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c313t-ae39441e20cd147da2c34f495ec6ee14cc2375ec6990a3d6489d92ee1ab5831f3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| OpenAccessLink | https://www.proquest.com/publiccontent/docview/2605265418?pq-origsite=%requestingapplication% |
| PQID | 2605265418 |
| PQPubID | 2048737 |
| PageCount | 17 |
| ParticipantIDs | proquest_journals_2605265418 crossref_primary_10_32604_cmc_2022_019291 crossref_citationtrail_10_32604_cmc_2022_019291 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-01-01 |
| PublicationDateYYYYMMDD | 2022-01-01 |
| PublicationDate_xml | – month: 01 year: 2022 text: 2022-01-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Henderson |
| PublicationPlace_xml | – name: Henderson |
| PublicationTitle | Computers, materials & continua |
| PublicationYear | 2022 |
| Publisher | Tech Science Press |
| Publisher_xml | – name: Tech Science Press |
| References | Kofler (ref1) 2016; 49 Zinko (ref5) 2021; 16 Batool (ref33) 2020; 14 Yager (ref44) 2015; 23 ref16 Broilo (ref31) 2010; 12 D'Angelo (ref32) 2021; 54 Koskela (ref9) 2004 Bul (ref11) 2011; 44 Lew (ref3) 2006; 2 Imran (ref21) 2013; 53 Ghrabat (ref37) 2019; 9 Anum (ref20) 2016; 3 Bhatt (ref7) 2021; 1 Jin (ref24) 2017; 45 Brits (ref26) 2007; 189 Manjunath (ref43) 2001; 11 Parsopoulos (ref22) 2002; 1 Sikora (ref40) 2001; 11 Saadatmand-Tarzjan (ref41) 2007; 37 Tian (ref19) 2018; 41 Bordogna (ref10) 1996; 82 Khan (ref34) 2020; 14 Kumar (ref29) 2020; 79 Cho (ref35) 2002; 32 Zhu (ref28) 2017; 375 Wickramasinghe (ref23) 2019; 15 Shi (ref27) 2017; 19 Okayama (ref30) 2008 Lu (ref17) 2010; 32 Dong (ref18) 2017; 21 Tao (ref12) 2006; 28 Sadad (ref25) 2020; 3 Baddeti (ref36) 2013; 10 Smeulders (ref2) 2000; 22 Datta (ref4) 2008; 40 Syam (ref39) 2012; 5 Djordjevic (ref13) 2007; 17 Yildizer (ref14) 2012; 39 Kennedy (ref15) 1995; 4 Wang (ref42) 2001; 23 Tao (ref8) 2007; 19 Kher (ref6) 2006; 15 Guha (ref38) 2019; 14 |
| References_xml | – volume: 16 start-page: 525 year: 2021 ident: ref5 article-title: The addition of images to eWOM in the travel industry: An examination of hotels, cruise ships and fast food reviews publication-title: Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer16030032 – start-page: 608 year: 2008 ident: ref30 publication-title: Neural Information Processing – volume: 54 start-page: 136 year: 2021 ident: ref32 article-title: GGA: A modified genetic algorithm with gradient-based local search for solving constrained optimization problems publication-title: Information Sciences doi: 10.1016/j.ins.2020.08.040 – volume: 1 start-page: 63 year: 2021 ident: ref7 article-title: A comprehensive review on content-based image retrieval system: Features and challenges publication-title: Data Science and Intelligent Applications doi: 10.1007/978-981-15-4474-3_7 – volume: 14 start-page: 1 year: 2020 ident: ref34 article-title: Human action recognition using fusion of multiview and deep features: An application to video surveillance publication-title: Multimedia Tools and Applications – volume: 14 start-page: 120 year: 2020 ident: ref33 article-title: Offline signature verification system: A novel technique of fusion of GLCM and geometric features using SVM publication-title: Multimedia Tools and Applications – volume: 15 start-page: 1017 year: 2006 ident: ref6 article-title: Relevance feedback for cbir: A new approach based on probabilistic feature weighting with positive and negative examples publication-title: IEEE Transactions on Image Processing doi: 10.1109/TIP.2005.863969 – volume: 53 start-page: 491 year: 2013 ident: ref21 article-title: An overview of particle swarm optimization variants publication-title: Procedia Engineering doi: 10.1016/j.proeng.2013.02.063 – volume: 375 start-page: 246 year: 2017 ident: ref28 article-title: Interpretation of users’ feedback via swarmed particles for content-based image retrieval publication-title: Information Sciences doi: 10.1016/j.ins.2016.09.021 – volume: 28 start-page: 1088 year: 2006 ident: ref12 article-title: Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/TPAMI.2006.134 – volume: 40 start-page: 1 year: 2008 ident: ref4 article-title: Image retrieval: Ideas, influences, and trends of the new age publication-title: ACM Computing Surveys doi: 10.1145/1348246.1348248 – volume: 1 start-page: 235 year: 2002 ident: ref22 article-title: Recent approaches to global optimization problems through particle swarm optimization publication-title: Natural Computing doi: 10.1023/A:1016568309421 – volume: 41 start-page: 49 year: 2018 ident: ref19 article-title: MPSO: Modified particle swarm optimization and its applications publication-title: Swarm and Evolutionary Computation doi: 10.1016/j.swevo.2018.01.011 – volume: 11 start-page: 696 year: 2001 ident: ref40 article-title: The mpeg-7 visual standard for content description-an overview publication-title: IEEE Transactions on Circuits and Systems for Video Technology doi: 10.1109/76.927422 – volume: 32 start-page: 452 year: 2002 ident: ref35 article-title: A human-oriented image retrieval system using interactive genetic algorithm publication-title: IEEE Transactions on Systems, Man and Cybernetics doi: 10.1109/TSMCA.2002.802812 – volume: 3 start-page: 49 year: 2016 ident: ref20 article-title: A hybrid particle swarm optimization (PSO) with Chi-square and stable mutation jump strategy publication-title: International Journal of Advanced and Applied Sciences doi: 10.21833/ijaas.2016.12.007 – volume: 10 start-page: 143 year: 2013 ident: ref36 article-title: An effective similarity measure via genetic algorithm for content based image retrieval with extensive features publication-title: International Arab Journal of Information Technology – volume: 5 start-page: 18 year: 2012 ident: ref39 article-title: An effective similarity measure via genetic algorithm for content-based image retrieval with extensive features publication-title: International Journal of Signal and Imaging Systems Engineering doi: 10.1504/IJSISE.2012.046742 – volume: 9 start-page: 1 year: 2019 ident: ref37 article-title: An effective image retrieval based on optimized genetic algorithm utilized a novel SVM-based convolutional neural network classifier publication-title: Human-centric Computing and Information Sciences doi: 10.1186/s13673-019-0191-8 – volume: 11 start-page: 703 year: 2001 ident: ref43 article-title: Color and texture descriptors publication-title: IEEE Transactions on Circuits and Systems for Video Technology doi: 10.1109/76.927424 – volume: 79 start-page: 22277 year: 2020 ident: ref29 article-title: An efficient content based image retrieval using an optimized neural network for medical application publication-title: Multimed Tools and Applications doi: 10.1007/s11042-020-08953-z – volume: 32 start-page: 921 year: 2010 ident: ref17 article-title: Experimental study of a new hybrid PSO with mutation for economic dispatch with non-smooth cost function publication-title: International Journal of Electrical Power & Energy Systems doi: 10.1016/j.ijepes.2010.03.001 – start-page: 508 year: 2004 ident: ref9 article-title: Use of image subset features in image retrieval with self-organizing maps – volume: 19 start-page: 568 year: 2007 ident: ref8 article-title: Negative samples analysis in relevance feedback publication-title: IEEE Transactions on Knowledge and Data Engineering doi: 10.1109/TKDE.2007.1003 – volume: 2 start-page: 1 year: 2006 ident: ref3 article-title: Content-based multimedia information retrieval: State of the art and challenges publication-title: ACM Transactions on Multimedia Computing, Communications, and Applications doi: 10.1145/1126004.1126005 – volume: 14 start-page: 1 year: 2019 ident: ref38 article-title: Deluge based genetic algorithm for feature selection publication-title: Evolutionary Intelligence – volume: 39 start-page: 2385 year: 2012 ident: ref14 article-title: Efficient content based image retrieval using multiple support vector machines ensemble publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2011.08.086 – volume: 19 start-page: 2804 year: 2017 ident: ref27 article-title: Structure-preserving image super-resolution via contextualized multitask learning publication-title: IEEE Transactions on Multimedia doi: 10.1109/TMM.2017.2711263 – volume: 17 start-page: 313 year: 2007 ident: ref13 article-title: An object- and user-driven system for semantic-based image annotation and retrieval publication-title: IEEE Transactions on Circuits and Systems for Video Technology doi: 10.1109/TCSVT.2007.890634 – volume: 37 start-page: 139 year: 2007 ident: ref41 article-title: A novel evolutionary approach for optimizing content-based image indexing algorithms publication-title: IEEE Transactions on Systems, Man, and Cybernetics doi: 10.1109/TSMCB.2006.880137 – volume: 49 start-page: 1 year: 2016 ident: ref1 article-title: User intent in multimedia search: A survey of the state of the art and future challenges publication-title: ACM Computing Surveys doi: 10.1145/2954930 – volume: 82 start-page: 201 year: 1996 ident: ref10 article-title: A user-adaptive neural network supporting a rule-based relevance feedback publication-title: Fuzzy Sets and Systems doi: 10.1016/0165-0114(95)00256-1 – volume: 44 start-page: 2109 year: 2011 ident: ref11 article-title: Content-based image retrieval with relevance feedback using random walks publication-title: Pattern Recognition doi: 10.1016/j.patcog.2011.03.016 – volume: 22 start-page: 1349 year: 2000 ident: ref2 article-title: Content-based image retrieval at the end of the early years publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.895972 – volume: 189 start-page: 1859 year: 2007 ident: ref26 article-title: Locating multiple optima using particle swarm optimization publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2006.12.066 – volume: 3 start-page: 180 year: 2020 ident: ref25 article-title: A review on multi-organs cancer detection using advanced machine learning techniques publication-title: Current Medical Imaging – volume: 12 start-page: 267 year: 2010 ident: ref31 article-title: A stochastic approach to image retrieval using relevance feedback and particle swarm optimization publication-title: IEEE Transactions on Multimedia doi: 10.1109/TMM.2010.2046269 – volume: 15 start-page: 5837 year: 2019 ident: ref23 article-title: Deep self-organizing maps for unsupervised image classification publication-title: IEEE Transactions on Industrial Informatics doi: 10.1109/TII.2019.2906083 – volume: 23 start-page: 2260 year: 2015 ident: ref44 article-title: Golden rule and other representative values for atanassov type intuitionistic membership grades publication-title: IEEE Transactions on Fuzzy Systems doi: 10.1109/TFUZZ.2015.2417895 – volume: 45 start-page: 1273 year: 2017 ident: ref24 article-title: Pathfinder: Application-aware distributed path computation in clouds publication-title: International Journal of Parallel Programming doi: 10.1007/s10766-016-0469-7 – volume: 4 start-page: 1942 year: 1995 ident: ref15 article-title: Particle swarm optimization publication-title: IEEE Int. Conf. on Neural Networks – volume: 23 start-page: 947 year: 2001 ident: ref42 article-title: Simplicity: Semantics-sensitive integrated matching for picture libraries publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.955109 – volume: 21 start-page: 5081 year: 2017 ident: ref18 article-title: Opposition-based particle swarm optimization with adaptive mutation strategy publication-title: Soft Computing doi: 10.1007/s00500-016-2102-5 – ident: ref16 doi: 10.1109/ACCESS.2019.2959325 |
| SSID | ssj0036390 |
| Score | 2.2539835 |
| Snippet | Searching images from the large image databases is one of the potential research areas of multimedia research. The most challenging task for nay CBIR system is... |
| SourceID | proquest crossref |
| SourceType | Aggregation Database Enrichment Source Index Database |
| StartPage | 963 |
| SubjectTerms | Evolutionary algorithms Feedback Genetic algorithms Heuristic methods Image management Image retrieval Multimedia Particle swarm optimization Performance measurement Support vector machines User feedback |
| Title | Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval |
| URI | https://www.proquest.com/docview/2605265418 |
| Volume | 70 |
| WOSCitedRecordID | wos000696956000014&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1546-2226 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0036390 issn: 1546-2226 databaseCode: BENPR dateStart: 20040101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 1546-2226 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0036390 issn: 1546-2226 databaseCode: PIMPY dateStart: 20040101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwED5By8DCG_GWBxaG0NhO85hQQa1AgqriJZgi5-ICoi3QFiT-PXeJA2JhYozsWFHufN_58d0HsK_Qb_phrryMGTKBRT4kTKwXoUWpUCssWO-351G3G9_dJT1Hj564a5VVTCwCdVntme9tUxBu5C_IO-YNzsIVS1jHR69vHmtI8VmrE9SYhToX3vJrUO-dXfTuq8isCY0LgmQzCD1F2FYeW1IC4wcNHHJBQ6UOOedJ5G-Y-h2lC-jpLP7vRy_BgktBRav0mWWYsaMVWKzkHYSb7atwdfrJdC7R_nDuacafojV4oCGnj0NxTPiXi0vmp7PniA7hYGbwWbRcmXJB-bA4G1LAol6s20VOvQY3nfb1yannNBg81FJPPWOZOSut8jGXQZQbsl_Qp1WVxdBaGSAqHfEDoZrReRjESZ4oajFZM9ayr9ehNnoZ2Q0QvsQokoixMQSJvm8SaWPMIhX3TRDqbBMa1S9P0RUoZ52MQUoLlcJIKRkpZSOlpZE24eD7jdeyOMcffXcqE6Vumk7SH4ts_d28DfM8Vrn3sgO16fjd7sIcfkyfJuM9qB-3u73LPedvXx_d4w4 |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LbxMxEB61KVK5UEqLCBTqQzlwWLJ-ZB8HhAI0SpQ0iqBF7WnxzjotIo-ShKL8KX4jM_sA9dJbDj2u7LXW9uf5xvbOfABHCv2mH2TKSzlCxjjkS8LYeSE6lAq1wjzq_Ws_HAyi8_N4uAF_qlgY_q2ysom5oc5myGfkDfa7FYtWR--vf3qsGsW3q5WERgGLnlv9pi3b4l33E83va6Xax6cfO16pKuChlnrpWcexoNIpHzNpwszSF5kR7RMcBs5Jg6h0yA9kp63OAhPFWayoxKbNSMuRpnY3YcsQ2P0abA27J8OLyvZr4vs8BLNpAk8RexYXo-Qi-aaBE06ZqNRb9qpieZsIb_NATm7tnfs2LI_hUelGi1aB-13YcNMnsFNJVIjSYu3Bl86KQ9LE8U25xOx8JVrjS-rC8moiPhCHZ-Izx9gz-kWbuDy1-EO0ylTrgnx60Z2Q0aVarD1GC3MfztbStadQm86m7hkIX2IYSsTIWqJ137exdBGmoYpG1gQ6rUOjmtQEyyTrrPUxTmizlcMgIRgkDIOkgEEd3vx747pIMHJH3YMKBElpahbJfwQ8v7v4ELY7pyf9pN8d9F7AQ263OEs6gNpy_su9hAd4s_y-mL8qUS3g27oR8xe1lDM7 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Hybrid+Evolutionary+Algorithm+Based+Relevance+Feedback+Approach+for+Image+Retrieval&rft.jtitle=Computers%2C+materials+%26+continua&rft.au=Mahmood%2C+Awais&rft.au=Imran%2C+Muhammad&rft.au=Irtaza%2C+Aun&rft.au=Abbas%2C+Qammar&rft.date=2022-01-01&rft.issn=1546-2226&rft.volume=70&rft.issue=1&rft.spage=963&rft.epage=979&rft_id=info:doi/10.32604%2Fcmc.2022.019291&rft.externalDBID=n%2Fa&rft.externalDocID=10_32604_cmc_2022_019291 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1546-2226&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1546-2226&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1546-2226&client=summon |