01096nam0-22003611i-450-99000801802040332120090806131023.00-262-55060-1000801802FED01000801802(Aleph)000801802FED0100080180220050304d2003----km-y0itay50------baengUSa---a---001yyNeural engineeringcomputation, representation, and dynamics in neurobiological systemsChris Eliasmith, Charles H. AndersonCambridge, Mass.MIT Pressc2003xii, 356 p.ill.24 cmComputational neuroscienceReti neuraliNeurobiologiaReti neuraliInformaticaNeuroscienza computazionale006.4Eliasmith,Chris285069Anderson,Charles H.285070ITUNINARICAUNIMARCBK990008018020403321006.4-ELI-13786SC1SC1Neural engineering754214UNINA04487nam 2201165z- 450 991059507260332120220916(CKB)5680000000080800(oapen)https://directory.doabooks.org/handle/20.500.12854/92145(oapen)doab92145(EXLCZ)99568000000008080020202209d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierTechniques and Applications of UAV-Based Photogrammetric 3D MappingBasel20221 online resource (294 p.)3-0365-5067-4 3-0365-5068-2 The book focuses on the techniques for UAV-based 3D mapping and its applications in varying fields since the explosive development of UAV-based photogrammetric 3D mapping and their wide applications from traditional surveying and mapping to other related fields have been witnessed in photogrammetry and remote sensing. In the last decade, unmanned aerial vehicle (UAV) images have become one of the most important remote sensing data sources for photogrammetric 3D mapping. Besides, the rapid development of recent techniques, e.g., SfM (Structure from Motion) for off-line image orientation, SLAM (Simultaneous Localization and Mapping) for on-line UAV navigation, and the deep learning (DL) embedded 3D reconstruction pipeline, has promoted UAV-based 3D mapping towards the direction of automation and intelligence. It is really worthy to collecting the cutting-edge techniques and reporting their promising applications.History of engineering & technologybicsscTechnology: general issuesbicssc3D point cloud3D reconstructionaerial triangulationaffine invariant featureaggregate semantic informationairborne LiDARBrown modelbuilding extractionbuilding façadebuilding footprintbuilding heightcamera self-calibrationcoal minecompound building reconstructionconvolutional neural networkcoplanar extractioncycle consistency inferencedeep convolutional neural networkdeep learningdeformation detectiondense shortcutdepth estimationdepth map fusiondetail preservingdigital photogrammetrydigital subsidence modeleffective feature distillationfeature pyramidgeometric topologyGF-7 imagehigh-frequency losshigh-resolution remote sensing imageshomography matriximage matchingindoor sceneleast square fittingLiDARlightweight image super-resolutionmatch pairmulti-viewmulti-view reconstructionmultiscale featuresn/aPatchMatchphotogrammetric mesh modelpoint cloudpoint cloudspolynomial modelpower linesred-black propagationrepetitive structuresemantic decompositionsemantic segmentationsingle image super-resolutionspatial eight-quadrant kernel convolutionstructure from motionsurface meshingsurface subsidencetexture mappingU-shaped residual networkUAV inspectionvery short baselinewide-baseline stereo imageHistory of engineering & technologyTechnology: general issuesJiang Wanshouedt1332328Jiang SanedtXiao XiongwuedtJiang WanshouothJiang SanothXiao XiongwuothBOOK9910595072603321Techniques and Applications of UAV-Based Photogrammetric 3D Mapping3040839UNINA