{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T09:49:02Z","timestamp":1762508942352,"version":"3.37.3"},"reference-count":73,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100014219","name":"National Science Fund for Distinguished Young Scholars","doi-asserted-by":"publisher","award":["2018-JCJQ-ZQ-046"],"award-info":[{"award-number":["2018-JCJQ-ZQ-046"]}],"id":[{"id":"10.13039\/501100014219","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Foundation","award":["SAST2021-040"],"award-info":[{"award-number":["SAST2021-040"]}]},{"name":"Civil Aviation Program","award":["B0201"],"award-info":[{"award-number":["B0201"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tgrs.2023.3267445","type":"journal-article","created":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T17:28:46Z","timestamp":1681925326000},"page":"1-16","source":"Crossref","is-referenced-by-count":14,"title":["All Adder Neural Networks for On-Board Remote Sensing Scene Classification"],"prefix":"10.1109","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4717-2304","authenticated-orcid":false,"given":"Ning","family":"Zhang","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0671-6777","authenticated-orcid":false,"given":"Guoqing","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0229-8424","authenticated-orcid":false,"given":"Jue","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"}]},{"given":"He","family":"Chen","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7747-523X","authenticated-orcid":false,"given":"Wenchao","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing, China"}]},{"given":"Liang","family":"Chen","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11554-009-0126-0"},{"key":"ref57","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2015.2504427"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013779"},{"key":"ref15","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/1869790.1869829"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref58","first-page":"1","article-title":"Automatic differentiation in PyTorch","author":"paszke","year":"2017","journal-title":"Proc NIPS Workshop"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01328"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.754"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/FPL.2019.00037"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00409"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SpaceComp.2019.00009"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00726"},{"key":"ref17","article-title":"Pruning filters for efficient ConvNets","author":"li","year":"2016","journal-title":"arXiv 1608 08710"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref19","first-page":"1737","article-title":"Deep learning with limited numerical precision","author":"gupta","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref18","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","author":"han","year":"2015","journal-title":"arXiv 1510 00149 [cs]"},{"key":"ref51","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"zagoruyko","year":"2016","journal-title":"arXiv 1612 03928"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3151405"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2937830"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00361"},{"key":"ref47","article-title":"Data augmentation using GANs","author":"dos santos tanaka","year":"2019","journal-title":"arXiv 1904 09135"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.06.043"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58542-6_23"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2752750"},{"key":"ref43","article-title":"Data-free adversarial distillation","author":"fang","year":"2019","journal-title":"arXiv 1912 11006"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_1"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10030282"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2964627"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.17485\/IJST\/v13i20.459","article-title":"Evolution of real-time onboard processing and classification of remotely sensed data","volume":"13","author":"mahendra","year":"2020","journal-title":"Indian J Sci Technol"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2021.106014"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3047130"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.01.004"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2020.12.008"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01275"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3390\/rs13030516"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2983560"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3059101"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3157671"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2783902"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2015.2496185"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2987060"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3042276"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.06.014"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2020.3005403"},{"key":"ref39","first-page":"1","article-title":"IntroVAE: Introspective variational autoencoders for photographic image synthesis","volume":"31","author":"huang","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","article-title":"An image is worth 16&#x00D7;16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"arXiv 2010 11929"},{"key":"ref71","article-title":"SGDR: Stochastic gradient descent with warm restarts","author":"loshchilov","year":"2016","journal-title":"arXiv 1608 03983"},{"key":"ref70","first-page":"1","article-title":"BinaryConnect: Training deep neural networks with binary weights during propagations","volume":"28","author":"courbariaux","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref73","first-page":"1","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref72","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref24","article-title":"Distilling the knowledge in a neural network","author":"hinton","year":"2015","journal-title":"ArXiv 1503 02531"},{"key":"ref68","article-title":"Explainable deep one-class classification","author":"liznerski","year":"2020","journal-title":"arXiv 2007 01760"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00154"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00224"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00360"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3194549"},{"key":"ref20","first-page":"10","article-title":"1.1 Computing&#x2019;s energy problem (and what we can do about it)","author":"horowitz","year":"2014","journal-title":"IEEE Int Solid-State Circuits Conf (ISSCC) Dig Tech Papers"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3152566"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2685945"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.matcom.2020.04.031"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3093914"},{"key":"ref21","article-title":"AdderNet and its minimalist hardware design for energy-efficient artificial intelligence","author":"wang","year":"2021","journal-title":"arXiv 2101 10015"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3075712"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2675998"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1080\/01431160903475266"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2015.2513443"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2011.608740"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1117\/1.JRS.10.035004"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2015.2475299"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/10006360\/10105644.pdf?arnumber=10105644","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T17:35:48Z","timestamp":1685381748000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10105644\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":73,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2023.3267445","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"type":"print","value":"0196-2892"},{"type":"electronic","value":"1558-0644"}],"subject":[],"published":{"date-parts":[[2023]]}}}