{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T01:07:29Z","timestamp":1789348049932,"version":"build-2803163510"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council (ARC) Discovery Early Career Researcher","doi-asserted-by":"publisher","award":["DE200101283"],"award-info":[{"award-number":["DE200101283"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ARC Discovery Project","award":["DP210102801"],"award-info":[{"award-number":["DP210102801"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tip.2024.3414132","type":"journal-article","created":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T18:09:16Z","timestamp":1720721356000},"page":"5273-5283","source":"Crossref","is-referenced-by-count":3,"title":["Scalable Deep Color Quantization: A Cluster Imitation Approach"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6916-4789","authenticated-orcid":false,"given":"Yunzhong","family":"Hou","sequence":"first","affiliation":[{"name":"School of Computing, the Australian National University, Canberra, ACT, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8929-7899","authenticated-orcid":false,"given":"Stephen","family":"Gould","sequence":"additional","affiliation":[{"name":"School of Computing, the Australian National University, Canberra, ACT, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1464-9500","authenticated-orcid":false,"given":"Liang","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computing, the Australian National University, Canberra, ACT, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/965145.801294"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/78.107417"},{"key":"ref3","volume-title":"Color Quantization","year":"2024"},{"key":"ref4","volume-title":"Pixel Art","year":"2024"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1201\/b18786"},{"key":"ref6","volume-title":"These Artists Are Giving Knitting a Place in Art History","year":"2024"},{"key":"ref7","volume-title":"Artist Combines Knitting and Digital Painting to Create Mesmerizing Artworks (10 Pics)","year":"2024"},{"key":"ref8","volume-title":"About Us\u2014Knitwise","year":"2024"},{"key":"ref9","volume-title":"Learning Multiple Layers of Features From Tiny Images","author":"A Krizhevsky","year":"2009"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01013"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-08-050753-8.50061-9"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3551389"},{"key":"ref15","article-title":"Clustering with deep learning: Taxonomy and new methods","author":"Aljalbout","year":"2018","journal-title":"arXiv:1801.07648"},{"key":"ref16","article-title":"A comprehensive survey on deep clustering: Taxonomy, challenges, and future directions","author":"Zhou","year":"2022","journal-title":"arXiv:2206.07579"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2024.3403155"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2745702"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974348.42"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.1999.779933"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/34.946985"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/146443.146475"},{"key":"ref24","first-page":"78","article-title":"An adaptive technique for spatial grayscale","volume":"17","author":"Floyd","year":"1976","journal-title":"Proc. Soc. Inf. Display"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/BF00337288"},{"key":"ref26","first-page":"3861","article-title":"Towards K-means-friendly spaces: Simultaneous deep learning and clustering","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yang"},{"key":"ref27","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","volume-title":"Proc. 33rd Int. Conf. Mach. Learn. (ICML)","volume":"48","author":"Xie"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.05.019"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_16"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3221290"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01348"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.556"},{"key":"ref33","first-page":"1","article-title":"Unsupervised multi-manifold clustering by learning deep representation","volume-title":"Proc. Workshops 31st AAAI Conf. Artif. Intell.","author":"Chen"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.612"},{"key":"ref35","first-page":"1558","article-title":"Learning discrete representations via information maximizing self-augmented training","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hu"},{"key":"ref36","first-page":"1","article-title":"Neural discrete representation learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Van Den Oord"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1603.08155"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00145"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58574-7_39"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01361"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1002\/nav.3800020109"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.626"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_44"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb01338.x"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00023"},{"key":"ref47","first-page":"215","article-title":"An analysis of single-layer networks in unsupervised feature learning","volume-title":"Proc. 14th Int. Conf. Artif. Intell. Statist.","author":"Coates"},{"issue":"7","key":"ref48","first-page":"3","article-title":"Tiny imagenet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref50","article-title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","author":"Geirhos","year":"2018","journal-title":"arXiv:1811.12231"},{"key":"ref51","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","author":"Krizhevsky"},{"key":"ref52","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref53","article-title":"SGDR: Stochastic gradient descent with warm restarts","author":"Loshchilov","year":"2016","journal-title":"arXiv:1608.03983"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.7000"},{"key":"ref55","volume-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.17487\/rfc2083"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/83\/10346232\/10596087.pdf?arnumber=10596087","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T05:09:57Z","timestamp":1727500197000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10596087\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/tip.2024.3414132","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}