000866303 000__ 04796cam\a2200541Ii\4500 000866303 001__ 866303 000866303 005__ 20230306145820.0 000866303 006__ m\\\\\o\\d\\\\\\\\ 000866303 007__ cr\cn\nnnunnun 000866303 008__ 190325s2019\\\\si\a\\\\ob\\\\100\0\eng\d 000866303 020__ $$a9789811365539$$q(electronic book) 000866303 020__ $$a9811365539$$q(electronic book) 000866303 020__ $$z9789811365522 000866303 035__ $$aSP(OCoLC)on1090540062 000866303 035__ $$aSP(OCoLC)1090540062 000866303 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dEBLCP 000866303 049__ $$aISEA 000866303 050_4 $$aQE33.2.R4 000866303 08204 $$a550.28$$223 000866303 1112_ $$aChina High Resolution Earth Observation Conference$$n(5th :$$d2018 :$$cChina) 000866303 24510 $$aProceedings of the 5th China High Resolution Earth Observation Conference (CHREOC 2018) /$$cLiheng Wang, Yirong Wu, Jianya Gong, editors. 000866303 24630 $$aCHREOC 2018 000866303 264_1 $$aingapore :$$bSpringer,$$c[2019] 000866303 300__ $$a1 online resource :$$billustrations. 000866303 336__ $$atext$$btxt$$2rdacontent 000866303 337__ $$acomputer$$bc$$2rdamedia 000866303 338__ $$aonline resource$$bcr$$2rdacarrier 000866303 4901_ $$aLecture notes in electrical engineering ;$$vvolume 552 000866303 504__ $$aIncludes bibliographical references and index. 000866303 5050_ $$aIntro; Contents; Satellite Energy Prediction and Autonomous Management Technology; Abstract; 1 Introduction; 2 The Design of Satellite Energy Autonomous Management System; 2.1 Solar Array Output Power Prediction; 2.2 Energy Autonomous Management; 2.3 Space-Ground Integration Energy Autonomous Management System; 3 Conclusion; References; Research on Key Technologies of Geosynchronous SAR Imaging System; Abstract; 1 Introduction; 2 GEOSAR Geometric Model; 2.1 GEOSAR Echo Signal Model; 2.2 GEOSAR Echo Two-Dimensional Frequency Domain Expression 000866303 5058_ $$a3 GEOSAR Image Processing Algorithm for Large Strabismus4 Simulation Experiment; 5 Conclusion; References; Sea-Land Segmentation Algorithm for SAR Images Based on Superpixel Merging; Abstract; 1 Introduction; 2 Superpixel Generation; 2.1 SLIC Algorithm; 2.2 Presegmentation Based on Modified SLIC; 2.2.1 Dissimilarity Measure; 2.2.2 Image Presegmentation; 3 Proposed Segmentation Method; 3.1 Superpixel Merging Rules; 3.1.1 Vicinity Rule; 3.1.2 Edge Rule; 3.1.3 Similarity Rule; 3.2 Coarse to Fine Strategy for Superpixel Merging; 3.2.1 Coarse Merging Stage (CMS); 3.2.2 Fine Merging Stage (FMS) 000866303 5058_ $$a3.3 Flowchart of the Proposed Algorithm4 Experimental Results and Discussion; 5 Conclusions; References; Vector Quantization: Timeline-Based Location Data Extraction and Route Fitting for Crowdsourcing; Abstract; 1 Introduction; 2 Related Work; 3 Contribution and Paper Structure; 3.1 Summary of Key Contributions; 3.2 Paper Structure; 4 Preliminaries; 4.1 System Overview; 4.2 Techniques; 4.2.1 Vector Quantization; 4.2.2 Cluster; 5 Of Model; 5.1 Algorithm of DB-SCAN Model; 5.2 Algorithm of Grid-K-Means Model; 6 Experiment and Theoretical Analysis; 7 Conclusion; References 000866303 5058_ $$aTarget Aspect Estimation in SAR Images via Two-Dimensional Entropic Thresholding and Radon TransformAbstract; 1 Introduction; 2 Image Processing; 2.1 2D Maximum Entropy Thresholding; 2.2 Radon Transform; 3 Aspect Estimation; 4 Experiments; 5 Conclusion; References; Signal Model and System Parameter Study for Geosynchronous Circular SAR; Abstract; 1 Introduction; 2 Geometry Model and Orbital Designing of Geo-CSAR; 2.1 Geo-CSAR Geometry Model; 2.2 Orbital Parameter Designing of Geo-CSAR; 3 Signal Model Analysis; 4 System Parameter Designing and Simulation 000866303 5058_ $$a4.1 Geo-CSAR System Parameter Designing4.2 Point Target Imaging Simulation; 5 Conclusion; Acknowledgements; References; Low-Light Remote Sensing Images Enhancement Algorithm Based on Fully Convolutional Neural Network; Abstract; 1 Introduction; 2 Method; 2.1 Description of Fully Convolutional Neural Network Structure; 2.2 Preparation of Dataset Used for Training; 2.3 Training Process of Fully Convolutional Neural Network; 2.4 Neural Network Training Based on Adam Optimizer; 3 Analysis of Numerical Results Based on SID Dataset; 4 Conclusion; References 000866303 506__ $$aAccess limited to authorized users. 000866303 588__ $$aOnline resource; title from PDF title page (viewed March 26, 2019). 000866303 650_0 $$aRemote-sensing images$$vCongresses. 000866303 650_0 $$aEarth sciences$$xRemote sensing$$vCongresses. 000866303 650_0 $$aRemote sensing$$vCongresses. 000866303 651_0 $$aEarth (Planet)$$xObservations$$vCongresses. 000866303 7001_ $$aWang, Liheng,$$eeditor. 000866303 7001_ $$aWu, Yirong,$$eeditor. 000866303 7001_ $$aGong, Jianya,$$eeditor. 000866303 830_0 $$aLecture notes in electrical engineering ;$$vv. 552. 000866303 852__ $$bebk 000866303 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-13-6553-9$$zOnline Access$$91397441.1 000866303 909CO $$ooai:library.usi.edu:866303$$pGLOBAL_SET 000866303 980__ $$aEBOOK 000866303 980__ $$aBIB 000866303 982__ $$aEbook 000866303 983__ $$aOnline 000866303 994__ $$a92$$bISE