检索结果-南通市图书馆

International Journal of Digital Earth 2021年第12期14卷 1897-1917页

作者： Lindy-Anne Siebritz Ahmad Desai Serena Coetzee Antony K.Cooper National Geo-spatial Information Department of AgricultureRural Development and Land ReformCape TownSouth Africa Department of Geography Geoinformatics and MeteorologyUniversity of PretoriaPretoriaSouth Africa Smart Places CSIRPretoriaSouth Africa

The Digital Earth vision foresees the availability and accessibility of geospatial information to achieve the goals of sustainable development,economic growth and social *** the case of urban areas,upto-date geospatial information is essential for managing a city towards achieving these *** rapid shift from rural to urban areas globally puts pressure on local governments and they often struggle to find and organise the resources required to collect and maintain geospatial information that can help to address urban growth challenges.A spatial data infrastructure(SDI)can facilitate the availability and accessibility of geospatial information towards addressing national objectives,however,the involvement of local governments in an SDI can be a *** this paper,we critique the role of municipalities against the backdrop of the developments of the South African SDI(SASDI)to *** critique identifies five high-level shortcomings of the SASDI that have led to the limited participation of *** on the shortcomings,we provide recommendations for capacitating municipalities through SASDI so that the Digital Earth vision can also be achieved for *** recommendations are aimed at involving the local sphere of government in a national SDI and are equally applicable to other countries.

关键词： SDI SASDI municipalities service delivery data governance

Evaluating the role of partnerships in increasing the use of big Earth data to support the Sustainable Development Goals:an Australian perspective

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Big Earth Data 2021年第4期5卷 527-556页

作者： Zaffar Sadiq Mohamed-Ghouse Cheryl Desha Abbas Rajabifard Michelle Blicavs Graeme Martin spatial vision Australia School of Engineering and Built Environment Cities Research InstituteGriffith UniversityBrisbaneAustralia Centre for spatial Data Infrastructures and Land Administration(CSDILA)at the University of Melbourne Australia Association of Consulting Surveyors Australia

Leaders are increasingly calling for improved decision support to manage human and environmental challenges in the 21^(st)*** 17 United Nations Sustainable Development Goals(SDGs)pro-vide a framing of these challenges,wherein 169 targets require significant data to be monitored and pursued ***,many targets are still not connected with big Earth data *** this conceptual paper,the authors sought to answer the question“How are partnerships influencing progress in using big Earth data to address the SDGs?”Using the Pivotal Principles for Digital Earth,we reflect on the geospatial sector’s partnering efforts and opportunities for enhancing the use of big Earth *** use Australia as a case study to explore partnering for action towards one or more *** conclude that partnerships are emerging for big Earth data use in addressing the SDGs,but much can still be done to harness the power of partnerships for transformative SDG *** propose four key enabling priorities:1)multiple-stakeholder collaboration,2)regular enactment of the problem-solving cycle,3)transparent and reliable georeferenced data,and 4)development and preservation of ***“next steps”are outlined for Australia,which can also benefit practitioners and leaders globally in problem-solving for the SDGs.

关键词： United Nations Sustainable Development Goals SDGs SDG-17 partnerships for decision support big Earth data Australia

Palmprint Recognition by Applying Wavelet-Based Kernel PCA

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Computer Science & Technology 2008年第5期23卷 851-861页

作者： Murat Ekinci Murat Aykut Computer vision Lab Department of Computer Engineering Karadeniz Technical University

This paper presents a wavelet-based kernel Principal Component Analysis （PCA） method by integrating the Daubechies wavelet representation of palm images and the kernel PCA method for palmprint recognition. Kernel PCA is a technique for nonlinear dimension reduction of data with an underlying nonlinear spatial structure. The intensity values of the palmprint image are first normalized by using mean and standard deviation. The palmprint is then transformed into the wavelet domain to decompose palm images and the lowest resolution subband coefficients are chosen for palm representation. The kernel PCA method is then applied to extract non-linear features from the subband coefficients. Finally, similarity measurement is accomplished by using weighted Euclidean linear distance-based nearest neighbor classifier. Experimental results on PolyU Palmprint Databases demonstrate that the proposed approach achieves highly competitive performance with respect to the published palmprint recognition approaches.

关键词： palmprint recognition kernel PCA wavelet transform biometrics pattern recognition

Towards geospatial semantic search:exploiting latent semantic relations in geospatial data

在线全文

学校读者我要写书评

暂无评论

International Journal of Digital Earth 2014年第1期7卷 17-37页

作者： Wenwen Li Michael FGoodchild Robert Raskin GeoDa Center for Geospatial Analysis and Computation School of Geographical Science and Urban PlanningArizona State UniversityTempeAZUSA Center for spatial Studies(spatial@UCSB) University of CaliforniaSanta BarbaraCAUSA NASA Jet Propulsion Laboratory PasadenaCAUSA

This paper reports our efforts to address the grand challenge of the Digital Earth vision in terms of intelligent data discovery from vast quantities of geo-referenced *** propose an algorithm combining LSA and a Two-Tier Ranking(LSATTR)algorithm based on revised cosine similarity to build a more efficient search engine-Semantic Indexing and Ranking(SIR)-for a semantic-enabled,more effective data *** addition to its ability to handle subject-based search,we propose a mechanism to combine geospatial taxonomy and Yahoo!GeoPlanet for automatic identification of location information from a spatial query and automatic filtering of datasets that are not spatially *** metadata set,in the format of ISO19115,from NASA's SEDAC(Socio-Economic Data Application Center)is used as the corpus of *** show that our semantic search engine SIR built on LSATTR methods outperforms existing keyword-matching techniques,such as Lucene,in terms of both recall and ***,the semantic associations among all existing words in the corpus are *** associations provide substantial support for automating the population of spatial *** expect this work to support the operationalization of the Digital Earth vision by advancing the semantic-based geospatial data discovery.

关键词： ontology geospatial semantics search engine Digital Earth similarity search effectiveness

New method for camera pose estimation based on line correspondence

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Technological Sciences) 2013年第11期56卷 2787-2797页

作者： LIU JinBo ZHANG XiaoHu LIU HaiBo YUAN Yun ZHU ZhaoKun YU QiFeng College of Aerospace Science and Engineering National University of Defense Technology Hunan Key Laboratory of Videometrics and vision Navigation

The key technology of the measuring method of pose shaking of unstable platform based on CCD lies in the camera pose estimation. A new method for camera pose estimation based on line correspondence is put forward in this paper. First, two appro- priate lines are selected in the space to establish a local coordinate system, the remaining lines form three-line sets with these two lines respectively and then the angle depth of the lines of the local coordinate system can be obtained by using the linearity of interpretation plane; then the invariance of included angle between spatial coordinate system and camera coordinate system during rigid transformation is used to establish a constraint equation set of angle depth of three lines similar to traditional P3P, and the corresponding angle depth of the third line in the set can be obtained linearly by variable substitution; finally, the rota- tion matrix can be expressed with quaternion and the pose parameters of camera in the space can be calculated by singular value decomposition （SVD）. The static experiment and dynamic experiment verify the accuracy and stability of the algorithm and that the camera pose shocking is within 1~ and the 3a error is superior to 0.3＇. The method in this paper can be directly used in the micro-vibration measurement of experimental platform and robot navigation and other fields and is of important theoretical significance and engineering application prospect.

关键词： unstable platform measurement of pose shaking line correspondence angle depth quaternion

Innovative Analysis Ready Data(ARD)product and process requirements,software system design,algorithms and implementation at the midstream as necessary-but-notsuffcient precondition of the downstream in a new notion of Space Economy 4.0-Part 1:Problem background in Artificial General Intelligence(AGI)

在线全文

学校读者我要写书评

暂无评论

Big Earth Data 2023年第3期7卷 455-693页

作者： Andrea Baraldi Luca D.Sapia Dirk Tiede Martin Sudmanns Hannah L.Augustin Stefan Lang spatial Services GmbH SalzburgAustria CGI Italy FrascatiItaly Department of Geoinformatics-Z_GIS University of SalzburgSalzburgAustria

Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched Analysis Ready Data(ARD)productpair and process gold standard as linchpin for success of a new notion of Space Economy *** be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,it is regarded as necessarybut-not-sufficient“horizontal”(enabling)precondition for:(I)Transforming existing EO big raster-based data cubes at the midstream segment,typically affected by the so-called data-rich information-poor syndrome,into a new generation of semanticsenabled EO big raster-based numerical data and vector-based categorical(symbolic,semi-symbolic or subsymbolic)information cube management systems,eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery.(II)Boosting the downstream segment in the development of an ever-increasing ensemble of“vertical”(deep and narrow,user-specific and domain-dependent)value–adding information products and services,suitable for a potentially huge worldwide market of institutional and private end-users of space *** the sake of readability,this paper consists of two *** the present Part 1,first,background notions in the remote sensing metascience domain are critically revised for harmonization across the multidisciplinary domain of cognitive *** short,keyword“information”is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed ***,buzzword“artificial intelligence”is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of ***,based on a betterdefined and better-understood vocabulary of multid

关键词： Artificial Narrow Intelligence big data cognitive science computer vision Earth observation essential climate variables Global Earth Observation System of(component)Systems inductive/deductive/hybrid inference Scene Classification Map Space Economy 4.0 radiometric corrections of optical imagery from atmospheric,topographic,adjacency and bidirectional reflectance distribution function effects semantic content-based image retrieval 2D spatial topology-preserving/retinotopic image mapping world ontology(synonym for conceptual/mental/perceptual model of the world)

An adaptive spatial clustering method for automatic brain MR image segmentation

在线全文

学校读者我要写书评

暂无评论

Progress in Natural Science:Materials International 2009年第10期19卷 1373-1382页

作者： Jingdan Zhang,Daoqing Dai Center for Computer vision and Department of Mathematics,Sun Yat-Sen(Zhongshan) University,Guangzhou 510275,China Center for Computer vision and Department of Mathematics Sun Yat-Sen (Zhongshan) University Guangzhou 510275 China

In this paper,an adaptive spatial clustering method is presented for automatic brain MR image segmentation,which is based on a competitive learning algorithm-self-organizing map(SOM).We use a pattern recognition approach in terms of feature generation and classifier ***,a multi-dimensional feature vector is constructed using local spatial ***,an adaptive spatial growing hierarchical SOM(ASGHSOM) is proposed as the classifier,which is an extension of SOM,fusing multi-scale segmentation with the competitive learning clustering algorithm to overcome the problem of overlapping grey-scale intensities on boundary ***,an adaptive spatial distance is integrated with ASGHSOM,in which local spatial information is considered in the clustering process to reduce the noise effiect and the classification *** proposed method is validated by extensive experiments using both simulated and real MR data with varying noise level,and is compared with the state-of-the-art algorithms.

关键词： Self-organizing map Growing hierarchical SOM Adaptive spatial distance Image segmentation MR images

Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Machine Intelligence Research 2024年第2期21卷 318-330页

作者： Yu-Cheng Chou Bowen Li Deng-Ping Fan Alan Yuille Zongwei Zhou Department of Computer Science Johns Hopkins UniversityBaltimore 21218USA Computer vision Lab ETH ZurichZurich 8001Switzerland

Creating large-scale and well-annotated datasets to train AI algorithms is crucial for automated tumor detection and ***,with limited resources,it is challenging to determine the best type of annotations when annotating massive amounts of unlabeled *** address this issue,we focus on polyps in colonoscopy videos and pancreatic tumors in abdominal CT scans;Both applications require significant effort and time for pixel-wise annotation due to the high dimensional nature of the data,involving either temporary or spatial *** this paper,we develop a new annotation strategy,termed Drag&Drop,which simplifies the annotation process to drag and *** annotation strategy is more efficient,particularly for temporal and volumetric imaging,than other types of weak annotations,such as per-pixel,bounding boxes,scribbles,ellipses and ***,to exploit our Drag&Drop annotations,we develop a novel weakly supervised learning method based on the watershed *** results show that our method achieves better detection and localization performance than alternative weak annotations and,more importantly,achieves similar performance to that trained on detailed per-pixel ***,we find that,with limited resources,allocating weak annotations from a diverse patient population can foster models more robust to unseen images than allocating per-pixel annotations for a small set of *** summary,this research proposes an efficient annotation strategy for tumor detection and localization that is less accurate than per-pixel annotations but useful for creating large-scale datasets for screening tumors in various medical modalities.

关键词： Weak annotation detection localization segmentation colonoscopy abdomen

THE OCULAR DOMINANCE DISTRIBUTIONS OF THE CELLS IN THE LATERAL SUPRASYLVIAN AREA BEFORE AND AFTER THE LESION OF VISUAL CORTEX AREAS 17, 18 AND 19 IN STRABISMIC CATS

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Science Bulletin 1992年第2期37卷 150-154页

作者：刘丹薛晋堂寿天德 vision Research Laboratory Department of Biology University of Science and Technology of China Hefei 230026 PRC

Among the visual cortex areas investigated, besides areas 17, 18 and 19, the lateral suprasylvian area (LS) is best studied. The cells in this area are mainly sensitive to the visual stimuli with the preferred moving direction. The responses to stationary stimuli are poor and the cells have no orientation selectivity. Most cells show spatial summation and

关键词： strabismus lateral suprasylvian ocular dominance.

Multimodality image registration and fusion using neural network

在线全文

学校读者我要写书评

暂无评论

Journal of Harbin Institute of Technology(New Series) 2003年第3期10卷 235-240页

作者： Mostafa G Mostafa Aly A Farag Edward Essock Computer vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USAComputer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USADept. of Psychology University of Louisville Louisville kY 40292 USA

Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.

关键词： data fusion image registration image interpolation neural network, 3-D model building