{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T03:23:32Z","timestamp":1784517812339,"version":"3.55.0"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Artif. Intell."],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1109\/tai.2021.3117537","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T16:48:45Z","timestamp":1633970925000},"page":"355-369","source":"Crossref","is-referenced-by-count":3,"title":["Assessment of the Clusterability of Data Using a Multimodal Convolutional Neural Network"],"prefix":"10.1109","volume":"3","author":[{"given":"Niko","family":"Reunanen","sequence":"first","affiliation":[{"name":"Hellon Ltd., Helsinki, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomi","family":"R\u00e4ty","sequence":"additional","affiliation":[{"name":"VTT Technical Research Centre of Finland Ltd., Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5035-7513","authenticated-orcid":false,"given":"Timo","family":"Lintonen","sequence":"additional","affiliation":[{"name":"VTT Technical Research Centre of Finland Ltd., Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juho J.","family":"Jokinen","sequence":"additional","affiliation":[{"name":"VTT Technical Research Centre of Finland Ltd., Espoo, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"47","article-title":"Clusterability detection and cluster initialization","volume-title":"Proc. Workshop Clustering High Dimensional Data Appl. 2nd SIAM Int. Conf. Data Mining","author":"Epter","year":"2002"},{"key":"ref2","first-page":"1","article-title":"Clusterability: A theoretical study","volume-title":"Proc. 12th Int. Conf. Artif. Intell. Statist.","volume":"5","author":"Ackerman","year":"2009"},{"key":"ref3","first-page":"1870","article-title":"Human cluster evaluation and formal quality measures: A comparative study","volume-title":"Proc. 34th Conf. Cogn. Sci. Soc.","author":"Lewis","year":"2012"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-45528-0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15986-2"},{"key":"ref6","first-page":"13","article-title":"To cluster, or not to cluster: An analysis of clusterability methods","volume-title":"Pattern Recognit.","volume":"88","author":"Adolfsson","year":"2019"},{"key":"ref7","author":"Tan","year":"2019","journal-title":"Introduction to Data Mining"},{"issue":"6","key":"ref8","first-page":"1332","article-title":"Clustering structure analysis in time-series data with density-based clusterability measure","volume-title":"IEEE\/CAA J. Automatica Sinica","volume":"6","author":"Jokinen","year":"2019"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07491-7_5"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2015.04.009"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2733381"},{"key":"ref12","article-title":"Deep density-based image clustering","volume-title":"Knowl.-Based Syst.","volume":"197","author":"Ren","year":"2020"},{"key":"ref13","first-page":"143","article-title":"Experiments with random projection","volume-title":"Proc. 16th Conf. Uncertainty Artif. Intell.","author":"Dasgupta","year":"2000"},{"key":"ref14","first-page":"69","article-title":"Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas","volume-title":"J. Multivariate Anal.","volume":"151","author":"Nagler","year":"2016"},{"key":"ref15","first-page":"103","article-title":"Clustering based on grid and local density with priority-based expansion for multi-density data","volume-title":"Inf. Sci.","volume":"468","author":"Dong","year":"2018"},{"key":"ref16","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Simonyan","year":"2015"},{"key":"ref17","first-page":"24","article-title":"Review on convolutional neural networks (CNN) in vegetation remote sensing","volume-title":"ISPRS J. Photogramm. Remote Sens.","volume":"173","author":"Kattenborn","year":"2021"},{"key":"ref18","first-page":"689","article-title":"Multimodal deep learning","volume-title":"Proc. 28th Int. Conf. Mach. Learn.","author":"Ngiam","year":"2011"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-014-1416-y"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/bf01025868"},{"issue":"2","key":"ref21","article-title":"Improved breast cancer classification through combining graph convolutional network and convolutional neural network","volume-title":"Inf. Process. Manage.","volume":"58","author":"Zhang","year":"2021"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2920267"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5555\/2999134.2999257"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2918284"},{"key":"ref25","first-page":"299","article-title":"Phoneme classification in reconstructed phase space with convolutional neural networks","volume-title":"Pattern Recognit. Lett.","volume":"135","author":"Wesley","year":"2020"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-70479-z"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-020-09825-6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref30","first-page":"111","article-title":"A theoretical analysis of feature pooling in visual recognition","volume-title":"Proc. 27th Int. Conf. Mach. Learn.","author":"Boureau","year":"2010"},{"key":"ref31","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Kingma","year":"2015"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref33","first-page":"I-115","article-title":"Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures","volume-title":"Proc. 30th Int. Conf. Mach. Learn.","volume":"28","author":"Bergstra","year":"2013"},{"key":"ref34","article-title":"An enhanced deep learning approach for brain cancer MRI images classification using residual networks","volume-title":"Artif. Intell. Med.","volume":"102","author":"Ismael"},{"key":"ref35","first-page":"112","article-title":"AutoTune: Automatically tuning convolutional neural networks for improved transfer learning","volume-title":"Neural Netw.","volume":"133","author":"Basha","year":"2021"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21557-5_13"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.211"},{"key":"ref38","volume-title":"Multivariate Analysis","author":"Mardia","year":"1979"},{"key":"ref39","article-title":"Is rotation forest the best classifier for problems with continuous features","author":"Bagnall","year":"2018"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2011.135"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2012.26"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s41060-018-0144-8"},{"key":"ref43","first-page":"75","article-title":"Clustering with SOM: U*C","volume-title":"Proc. Workshop Self-Organizing Maps","author":"Ultsch","year":"2005"},{"key":"ref44","article-title":"UCI machine learning repository","author":"Dua","year":"2017"},{"key":"ref45","volume-title":"R: A Language and Environment for Statistical Computing","year":"2020"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220042"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1002\/0471434159"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2007.4409061"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2012.2229980"},{"key":"ref50","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref51","first-page":"79","article-title":"Reshaping inputs for convolutional neural network: Some common and uncommon methods","volume-title":"Pattern Recognit.","volume":"93","author":"Ghosh"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-018-0951-8"},{"issue":"5","key":"ref53","article-title":"A double-density clustering method based on nearest to first in strategy","volume":"12","author":"Liu","year":"2020"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/s10959-013-0491-2"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37456-2_14"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972795.55"},{"issue":"5","key":"ref57","first-page":"304","article-title":"International application of a new probability algorithm for the diagnosis of coronary artery disease","volume-title":"Amer. J. Cardiol.","volume":"64","author":"Detrano","year":"1989"},{"issue":"1","key":"ref58","first-page":"652","article-title":"A novel clustering approach: Artificial bee colony (ABC) algorithm","volume-title":"Appl. Soft Comput.","volume":"11","author":"Karaboga","year":"2011"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2014.12.038"}],"container-title":["IEEE Transactions on Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9078688\/9781840\/09566791.pdf?arnumber=9566791","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T01:10:06Z","timestamp":1755911406000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9566791\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6]]},"references-count":59,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tai.2021.3117537","relation":{},"ISSN":["2691-4581"],"issn-type":[{"value":"2691-4581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6]]}}}