{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:26:44Z","timestamp":1740122804500,"version":"3.37.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T00:00:00Z","timestamp":1600905600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T00:00:00Z","timestamp":1600905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s11042-020-09765-x","type":"journal-article","created":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T01:30:13Z","timestamp":1600911013000},"page":"3793-3808","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A hybrid shape-based image clustering using time-series analysis"],"prefix":"10.1007","volume":"80","author":[{"given":"Atreyee","family":"Mondal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nilanjan","family":"Dey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Fong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3217-6185","authenticated-orcid":false,"given":"Amira S.","family":"Ashour","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,24]]},"reference":[{"key":"9765_CR1","doi-asserted-by":"crossref","unstructured":"Aghabozorgi S, Ying Wah T, Herawan T, Jalab HA, Shaygan MA, Jalali A (2014) A hybrid algorithm for clustering of time series data based on affinity search technique. Sci World J","DOI":"10.1155\/2014\/562194"},{"key":"9765_CR2","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.is.2015.04.007","volume":"53","author":"S Aghabozorgi","year":"2015","unstructured":"Aghabozorgi S, Shirkhorshidi AS, Wah TY (2015) Time-series clustering\u2013a decade review. Inf Syst 53:16\u201338","journal-title":"Inf Syst"},{"issue":"3","key":"9765_CR3","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1093\/bib\/bbn058","volume":"10","author":"B Andreopoulos","year":"2009","unstructured":"Andreopoulos B, An A, Wang X, Schroeder M (2009) A roadmap of clustering algorithms: finding a match for a biomedical application. Brief Bioinform 10(3):297\u2013314","journal-title":"Brief Bioinform"},{"issue":"9\u201310","key":"9765_CR4","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1016\/S0167-8655(03)00002-3","volume":"24","author":"N Arica","year":"2003","unstructured":"Arica N, Vural FTY (2003) BAS: a perceptual shape descriptor based on the beam angle statistics. Pattern Recogn Lett 24(9\u201310):1627\u20131639","journal-title":"Pattern Recogn Lett"},{"issue":"6","key":"9765_CR5","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1007\/s10043-009-0119-z","volume":"16","author":"AN Avanaki","year":"2009","unstructured":"Avanaki AN (2009) Exact global histogram specification optimized for structural similarity. Opt Rev 16(6):613\u2013621","journal-title":"Opt Rev"},{"issue":"1","key":"9765_CR6","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1109\/TPAMI.2005.21","volume":"27","author":"I Bartolini","year":"2005","unstructured":"Bartolini I, Ciaccia P, Patella M (2005) Warp: accurate retrieval of shapes using phase of fourier descriptors and time warping distance. IEEE Trans Pattern Anal Mach Intell 27(1):142\u2013147","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"9765_CR7","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1109\/34.993558","volume":"24","author":"S Belongie","year":"2002","unstructured":"Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal Mach Intell 24(4):509\u2013522","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"9765_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1943371.1943381","volume":"36","author":"PS Bishnu","year":"2011","unstructured":"Bishnu PS, Bhattacherjee V (2011) Application of k-medoids with kd-tree for software fault prediction. ACM SIGSOFT Software Eng Notes 36(2):1\u20136","journal-title":"ACM SIGSOFT Software Eng Notes"},{"key":"9765_CR9","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1007\/978-3-642-13772-3_2","volume-title":"International Conference Image Analysis and Recognition","author":"D Brunet","year":"2010","unstructured":"Brunet D, Vrscay ER, Wang Z (2010) Structural similarity-based approximation of signals and images using orthogonal bases. In: International Conference Image Analysis and Recognition. Springer, Berlin, pp 11\u201322"},{"issue":"11","key":"9765_CR10","first-page":"35","volume":"125","author":"S Chormunge","year":"2015","unstructured":"Chormunge S, Jena S (2015) Efficiency and effectiveness of clustering algorithms for high dimensional data. Int J Comput Appl 125(11):35\u201340","journal-title":"Int J Comput Appl"},{"volume-title":"Classification and clustering in biomedical signal processing","year":"2016","key":"9765_CR11","unstructured":"Dey N, Ashour A (eds) (2016) Classification and clustering in biomedical signal processing. IGI global, Hershey"},{"issue":"1","key":"9765_CR12","doi-asserted-by":"publisher","first-page":"60","DOI":"10.3390\/jimaging1010060","volume":"1","author":"N Dey","year":"2015","unstructured":"Dey N, Ashour AS, Beagum S, Pistola DS, Gospodinov M, Gospodinova \u0415P, Tavares JMR (2015) Parameter optimization for local polynomial approximation based intersection confidence interval filter using genetic algorithm: an application for brain MRI image de-noising. J Imaging 1(1):60\u201384","journal-title":"J Imaging"},{"key":"9765_CR13","first-page":"978","volume":"10","author":"N Dey","year":"2016","unstructured":"Dey N, Bhateja V, Hassanien AE (2016) Medical imaging in clinical applications. Springer Int Publishing 10:978\u2013973","journal-title":"Springer Int Publishing"},{"issue":"2","key":"9765_CR14","doi-asserted-by":"publisher","first-page":"51","DOI":"10.3390\/sym10020051","volume":"10","author":"N Dey","year":"2018","unstructured":"Dey N, Rajinikanth V, Ashour AS, Tavares JMR (2018) Social group optimization supported segmentation and evaluation of skin melanoma images. Symmetry 10(2):51","journal-title":"Symmetry"},{"issue":"24","key":"9765_CR15","doi-asserted-by":"publisher","first-page":"31545","DOI":"10.1007\/s11042-018-6148-5","volume":"77","author":"D Dharma","year":"2018","unstructured":"Dharma D (2018) Coral reef image\/video classification employing novel octa-angled pattern for triangular sub region and pulse coupled convolutional neural network (PCCNN). Multimed Tools Appl 77(24):31545\u201331579","journal-title":"Multimed Tools Appl"},{"key":"9765_CR16","first-page":"157","volume-title":"International Workshop on Advanced Analysis and Learning on Temporal Data","author":"M Dupont","year":"2015","unstructured":"Dupont M, Marteau PF (2015) Coarse-dtw for sparse time series alignment. In: International Workshop on Advanced Analysis and Learning on Temporal Data. Springer, Cham, pp 157\u2013172"},{"key":"9765_CR17","unstructured":"Hatami N, Gavet Y, Debayle J (2018) Classification of time-series images using deep convolutional neural networks. In Tenth International Conference on Machine Vision (ICMV 2017) vol 10696. International Society for Optics and Photonics, p 106960Y"},{"issue":"3","key":"9765_CR18","doi-asserted-by":"publisher","first-page":"58","DOI":"10.4018\/IJACI.2017070104","volume":"8","author":"S Hemalatha","year":"2017","unstructured":"Hemalatha S, Anouncia SM (2017) Unsupervised segmentation of remote sensing images using FD based texture analysis model and ISODATA. Int J Ambient Comput Intell (IJACI) 8(3):58\u201375","journal-title":"Int J Ambient Comput Intell (IJACI)"},{"issue":"6","key":"9765_CR19","first-page":"2088","volume":"6","author":"S Hore","year":"2016","unstructured":"Hore S, Chakraborty S, Chatterjee S, Dey N, Ashour AS, Van Chung L, Le DN (2016) An integrated interactive technique for image segmentation using stack based seeded region growing and Thresholding. Int J Electric Comput Eng 6(6):2088\u20138708","journal-title":"Int J Electric Comput Eng"},{"issue":"4","key":"9765_CR20","doi-asserted-by":"publisher","first-page":"19","DOI":"10.4018\/IJACI.2017100102","volume":"8","author":"A Jain","year":"2017","unstructured":"Jain A, Bhatnagar V (2017) Concoction of ambient intelligence and big data for better patient ministration services. International Journal of Ambient Computing and Intelligence (IJACI) 8(4):19\u201330","journal-title":"International Journal of Ambient Computing and Intelligence (IJACI)"},{"key":"9765_CR21","unstructured":"Keogh EJ, Pazzani MJ (1998) An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback. In: Kdd, vol 98, pp 239-243"},{"key":"9765_CR22","first-page":"43","volume":"34","author":"W Kim","year":"2009","unstructured":"Kim W (2009) Parallel clustering algorithms: survey. Parallel Algorithms Spring 34:43","journal-title":"Parallel Algorithms Spring"},{"issue":"2","key":"9765_CR23","doi-asserted-by":"publisher","first-page":"47","DOI":"10.4018\/IJACI.2016070103","volume":"7","author":"DR Kishor","year":"2016","unstructured":"Kishor DR, Venkateswarlu NB (2016) A novel hybridization of expectation-maximization and k-means algorithms for better clustering performance. Int J Ambient Comput Intell (IJACI) 7(2):47\u201374","journal-title":"Int J Ambient Comput Intell (IJACI)"},{"issue":"11","key":"9765_CR24","doi-asserted-by":"publisher","first-page":"1857","DOI":"10.1016\/j.patcog.2005.01.025","volume":"38","author":"TW Liao","year":"2005","unstructured":"Liao TW (2005) Clustering of time series data\u2014a survey. Pattern Recogn 38(11):1857\u20131874","journal-title":"Pattern Recogn"},{"issue":"3","key":"9765_CR25","doi-asserted-by":"publisher","first-page":"2427","DOI":"10.1007\/s11277-017-4981-x","volume":"98","author":"NAB Mary","year":"2018","unstructured":"Mary NAB, Dejey D (2018) Classification of coral reef submarine images and videos using a novel Z with tilted Z local binary pattern (Z\u2295 TZLBP). Wirel Pers Commun 98(3):2427\u20132459","journal-title":"Wirel Pers Commun"},{"key":"9765_CR26","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.jvcir.2017.09.008","volume":"49","author":"NAB Mary","year":"2017","unstructured":"Mary NAB, Dharma D (2017) Coral reef image classification employing improved LDP for feature extraction. J Vis Commun Image Represent 49:225\u2013242","journal-title":"J Vis Commun Image Represent"},{"key":"9765_CR27","doi-asserted-by":"crossref","unstructured":"Paparrizos J, Gravano L (2015) K-shape: efficient and accurate clustering of time series. In:Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data pp 1855-1870.","DOI":"10.1145\/2723372.2737793"},{"key":"9765_CR28","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1016\/j.procs.2016.08.106","volume":"96","author":"N Vaughan","year":"2016","unstructured":"Vaughan N and Gabrys B (2016) Comparing and combining time series trajectories using dynamic time warping. Procedia Computer Science 96:465\u2013474","journal-title":"Procedia Computer Science"},{"issue":"4","key":"9765_CR29","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1007\/s10852-005-9022-1","volume":"5","author":"AP Reynolds","year":"2006","unstructured":"Reynolds AP, Richards G, de la Iglesia B, Rayward-Smith VJ (2006) Clustering rules: a comparison of partitioning and hierarchical clustering algorithms. J Mathematical Modell Algorithms 5(4):475\u2013504","journal-title":"J Mathematical Modell Algorithms"},{"issue":"1","key":"9765_CR30","doi-asserted-by":"publisher","first-page":"e0210236","DOI":"10.1371\/journal.pone.0210236","volume":"14","author":"MZ Rodriguez","year":"2019","unstructured":"Rodriguez MZ, Comin CH, Casanova D, Bruno OM, Amancio DR, Costa LDF, Rodrigues FA (2019) Clustering algorithms: A comparative approach. PLoS One 14(1):e0210236","journal-title":"PLoS One"},{"issue":"12","key":"9765_CR31","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1007\/s00521-016-2645-5","volume":"29","author":"SC Satapathy","year":"2018","unstructured":"Satapathy SC, Raja NSM, Rajinikanth V, Ashour AS, Dey N (2018) Multi-level image thresholding using Otsu and chaotic bat algorithm. Neural Comput Applic 29(12):1285\u20131307","journal-title":"Neural Comput Applic"},{"issue":"1","key":"9765_CR32","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1023\/A:1008102926703","volume":"35","author":"K Siddiqi","year":"1999","unstructured":"Siddiqi K, Shokoufandeh A, Dickinson SJ, Zucker SW (1999) Shock graphs and shape matching. Int J Comput Vis 35(1):13\u201332","journal-title":"Int J Comput Vis"},{"issue":"2","key":"9765_CR33","doi-asserted-by":"publisher","first-page":"57","DOI":"10.4018\/IJSE.2015070104","volume":"6","author":"I Trabelsi","year":"2015","unstructured":"Trabelsi I, Bouhlel MS (2015) Feature selection for GUMI kernel-based SVM in speech emotion recognition. Int J Synthetic Emotions (IJSE) 6(2):57\u201368","journal-title":"Int J Synthetic Emotions (IJSE)"},{"issue":"3","key":"9765_CR34","doi-asserted-by":"publisher","first-page":"15","DOI":"10.4018\/IJACI.2018070102","volume":"9","author":"S Vengadeswaran","year":"2018","unstructured":"Vengadeswaran S, Balasundaram SR (2018) An optimal data placement strategy for improving system performance of massive data applications using graph clustering. Int J Ambient Comput Intell (IJACI) 9(3):15\u201330","journal-title":"Int J Ambient Comput Intell (IJACI)"},{"key":"9765_CR35","unstructured":"Vlachos M, Lin J, Keogh E, Gunopulos D (2003) A wavelet-based anytime algorithm for k-means clustering of time series. In: In proc. workshop on clustering high dimensionality data and its applications"},{"issue":"4","key":"9765_CR36","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, HR S, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"9765_CR37","doi-asserted-by":"crossref","unstructured":"Wang Z, Li Q, Shang X (2007) Perceptual image coding based on a maximum of minimal structural similarity criterion. In: 2007 IEEE International Conference on Image Processing, vol 2. IEEE, pp II-121","DOI":"10.1109\/ICIP.2007.4379107"},{"key":"9765_CR38","unstructured":"Yang B, Fu X, Sidiropoulos ND, Hong M (2017) Towards k-means-friendly spaces: simultaneous deep learning and clustering. In: International conference on machine learning, pp 3861-3870"},{"key":"9765_CR39","doi-asserted-by":"crossref","unstructured":"Yankov D, Keogh E (2006) Manifold clustering of shapes. In: Sixth International Conference on Data Mining (ICDM'06) (pp 1167-1171). IEEE","DOI":"10.1109\/ICDM.2006.101"},{"issue":"1","key":"9765_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.patcog.2003.07.008","volume":"37","author":"D Zhang","year":"2004","unstructured":"Zhang D, Lu G (2004) Review of shape representation and description techniques. Pattern Recogn 37(1):1\u201319","journal-title":"Pattern Recogn"},{"issue":"10","key":"9765_CR41","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1109\/TKDE.2006.162","volume":"18","author":"ML Zhang","year":"2006","unstructured":"Zhang ML, Zhou ZH (2006) Multilabel neural networks with applications to functional genomics and text categorization. IEEE Trans Knowl Data Eng 18(10):1338\u20131351","journal-title":"IEEE Trans Knowl Data Eng"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09765-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09765-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09765-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T07:40:00Z","timestamp":1632469200000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09765-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,24]]},"references-count":41,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["9765"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09765-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,9,24]]},"assertion":[{"value":"19 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}