{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:07:41Z","timestamp":1774541261904,"version":"3.50.1"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["61973285"],"award-info":[{"award-number":["61973285"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["62076226"],"award-info":[{"award-number":["62076226"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["61873249"],"award-info":[{"award-number":["61873249"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tgrs.2022.3220748","type":"journal-article","created":{"date-parts":[[2022,11,9]],"date-time":"2022-11-09T20:36:51Z","timestamp":1668026211000},"page":"1-14","source":"Crossref","is-referenced-by-count":21,"title":["MO-CNN: Multiobjective Optimization of Convolutional Neural Networks for Hyperspectral Image Classification"],"prefix":"10.1109","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8298-7715","authenticated-orcid":false,"given":"Xiaobo","family":"Liu","sequence":"first","affiliation":[{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, School of Automation, China University of Geosciences, Wuhan, China"}]},{"given":"Xin","family":"Gong","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, School of Automation, China University of Geosciences, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9613-1659","authenticated-orcid":false,"given":"Antonio","family":"Plaza","sequence":"additional","affiliation":[{"name":"Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Polit&#x00E9;cnica, University of Extremadura, C&#x00E1;ceres, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0020-6503","authenticated-orcid":false,"given":"Zhihua","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan, China"}]},{"given":"Xiao","family":"Xiao","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, School of Automation, China University of Geosciences, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6783-2176","authenticated-orcid":false,"given":"Xinwei","family":"Jiang","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, School of Automation, China University of Geosciences, Wuhan, China"}]},{"given":"Xiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, School of Automation, China University of Geosciences, Wuhan, China"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2616489"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS47720.2021.9554961"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2019.8790145"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"key":"ref31","first-page":"1","article-title":"NEMO: Neuro-evolution with multiobjective optimization of deep neural network for speed and accuracy","volume":"1","author":"kim","year":"2017","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/rs13061082"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2019.2912563"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.11.025"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321729"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321735"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS47720.2021.9553652"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00257"},{"key":"ref12","first-page":"1","article-title":"Neural architecture search with reinforcement learning","author":"zoph","year":"2017","journal-title":"Proc 5th Int Conf Learn Represent (ICML)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3005623"},{"key":"ref14","article-title":"SMASH: One-shot model architecture search through HyperNetworks","author":"brock","year":"2017","journal-title":"Arxiv 1708 05344"},{"key":"ref15","first-page":"7827","article-title":"Neural architecture optimization","author":"luo","year":"2018","journal-title":"Proc Conf Neural Inf Process Syst (NIPS)"},{"key":"ref16","first-page":"1","article-title":"DARTS: Differentiable architecture search","author":"liu","year":"2019","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ITNEC52019.2021.9586824"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3059510"},{"key":"ref19","first-page":"1","article-title":"Understanding and robustifying differentiable architecture search","author":"zela","year":"2020","journal-title":"Int Conf Learn Represent (ICLR)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00190"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3052048"},{"key":"ref27","first-page":"4095","article-title":"Efficient neural architecture search via parameters sharing","author":"pham","year":"2018","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3102034"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2890127"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2910603"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2021.3061466"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3058321"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2951433"},{"key":"ref9","first-page":"1","article-title":"Designing neural network architectures using reinforcement learning","author":"baker","year":"2017","journal-title":"Proc 5th Int Conf Learn Represent (ICLR)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3102-9"},{"key":"ref20","first-page":"1554","article-title":"Stabilizing differentiable architecture search via perturbation-based regularization","author":"chen","year":"2020","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_28"},{"key":"ref21","article-title":"DARTS: Improved differentiable architecture search with early stopping","author":"liang","year":"2019","journal-title":"arXiv 1909 06035"},{"key":"ref42","first-page":"126","article-title":"A self-adaptive multi-objective optimization algorithm based on the Pareto&#x2019;s nondominated sets","author":"wang","year":"2012","journal-title":"Proc Symp ICT Energy Efficiency Workshop Inf Theory Secur (CIICT)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.154"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CCDC.2015.7162243"},{"key":"ref23","first-page":"1","article-title":"DARTS: Robustly stepping out of performance collapse without indicators","author":"chu","year":"2021","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00238"},{"key":"ref25","first-page":"19","article-title":"Progressive neural architecture search","author":"liu","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9633014\/09943534.pdf?arnumber=9943534","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:30:47Z","timestamp":1670873447000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9943534\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2022.3220748","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}