{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T11:11:45Z","timestamp":1757589105043},"reference-count":8,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2019,3,1]]},"DOI":"10.1587\/transinf.2018edl8158","type":"journal-article","created":{"date-parts":[[2019,2,28]],"date-time":"2019-02-28T17:38:30Z","timestamp":1551375510000},"page":"655-658","source":"Crossref","is-referenced-by-count":4,"title":["Millimeter-Wave InSAR Target Recognition with Deep Convolutional Neural Network"],"prefix":"10.1587","volume":"E102.D","author":[{"given":"Yilu","family":"MA","sequence":"first","affiliation":[{"name":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuehua","family":"LI","sequence":"additional","affiliation":[{"name":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] C. Bentes, D. Velotto, and B. Tings, \u201cShip Classification in TerraSAR-X Images With Convolutional Neural Networks,\u201d IEEE J. Ocean. Eng., vol.43, no.1, pp.258-266, 2018. 10.1109\/joe.2017.2767106","DOI":"10.1109\/JOE.2017.2767106"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] J. Chen, Y. Li, J. Wang, Y. Li, and Y. Zhang, \u201cAn accurate imaging algorithm for millimeter wave synthetic aperture imaging radiometer in near-field,\u201d Progress In Electromagnetics Research, vol.141, pp.517-535, 2013. 10.2528\/pier13060702","DOI":"10.2528\/PIER13060702"},{"key":"3","unstructured":"[3] H.W. Yun, J.R. Kim, C.Y. Soo, et al., \u201cThe application of InSAR time series for landcover classification,\u201d IEEE Synthetic Aperture Radar, pp.308-311, 2013."},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] M.E. Engdahl, J. Pulliainen, and M. Hallikainen, \u201cCombined land-cover classification and stem volume estimation using multitemporal ERS tandem INSAR data,\u201d 2003 IEEE International Geoscience and Remote Sensing Symposium, pp.1936-1938, 2003. 10.1109\/igarss.2003.1294298","DOI":"10.1109\/IGARSS.2003.1294298"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] Y. LeCun, K. Kavukcuoglu, and C. Farabet, \u201cConvolutional networks and applications in vision,\u201d Proc. 2010 IEEE International Symposium on Circuits and Systems, pp.253-256, 2010. 10.1109\/iscas.2010.5537907","DOI":"10.1109\/ISCAS.2010.5537907"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] S. Chen, H. Wang, F. Xu, and Y.-Q. Jin, \u201cTarget Classification Using the Deep Convolutional Networks for SAR Images,\u201d IEEE Trans. Geosci. Remote Sens., vol.54, no.8, pp.4806-4817, 2016. 10.1109\/tgrs.2016.2551720","DOI":"10.1109\/TGRS.2016.2551720"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] Y. Zhang, Y. Li, and S. Safavi-naeini, \u201cA Spectrum-Based Saliency Detection Algorithm for Millimeter-Wave InSAR Imaging with Sparse Sensing,\u201d IEICE Trans. Inf. &amp; Syst., vol.E100.D, no.2, pp.388-391, 2017. 10.1587\/transinf.2016edl8119","DOI":"10.1587\/transinf.2016EDL8119"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] B. Zhu, J.Z. Liu, S.F. Cauley, B.R. Rosen, and M.S. Rosen, \u201cImage reconstruction by domain-transform manifold learning,\u201d Nature., vol.555, no.7697, pp.487-492, 2018. 10.1038\/nature25988","DOI":"10.1038\/nature25988"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E102.D\/3\/E102.D_2018EDL8158\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,2]],"date-time":"2019-03-02T00:18:01Z","timestamp":1551485881000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E102.D\/3\/E102.D_2018EDL8158\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,1]]},"references-count":8,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2018edl8158","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,1]]}}}