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A Multi-representation Spatial Data Model [chapter]

Sheng Zhou, Christopher B. Jones
2003 Lecture Notes in Computer Science  
We present a multi-representation spatial data model based on this approach and illustrate the implementation of multi-representation geometry in association with an online web demonstration.  ...  Ideally a spatial database will provide access to spatial data across a continuous range of resolution and multiple levels of generalisation.  ...  In the remainder of this paper, we present a multi-representation spatial data model based on multi-representation geometry.  ... 
doi:10.1007/978-3-540-45072-6_23 fatcat:ogtd2ixugrdndkf63rg3s35k4m

Multiple Representations for Cartographic Objects in a Multi-Scale Tree-An Intelligent Graphical Zoom. Computers and Graphics: Special Issue on Modelling and Visualization of Spatial Data in SIG

Referências Albrecht, J Andrienko, N Andrienko, G Crete, Greece, C Stephanidis, J Jacko, W Cartwright, G Hunter, C De Souza, S Barbosa, R Prates (+4 others)
1997 Cartography and Geographic Information Science   unpublished
A framework for analyzing and understanding online communities.  ...  CASA -Centre for Advanced Spatial Analysis. Working Paper Series, 2002. Traynor, C.; Williams, M. G. Why are Geographic Information Systems Hard to Use?  ...  Geographic Task Models for Geographic Information Processing. In: Meeting on Fundamental Questions in Geographic Information Science, 2001, Manchester, UK, Duckham, M. and Worboys M.F.  ... 

A Seamless Constraint Model of Multi-Scale Representation of Geographical Information

Di Chen, Han Yue, Xinyan Zhu
2015 International Journal of Security and Its Applications  
At present, it has become a hot issue to provide a multi-representation mechanism and build multi-scale spatial databases in the field of GIS.  ...  In this paper, we introduce the concepts of homonymous points and homonymous entities based on innate characteristics of spatial data and put forward a seamless constraint model of multi-scale representation  ...  Broadly defined, the spatial data representation model can be formalized with a 5-tuple (4).  ... 
doi:10.14257/ijsia.2015.9.8.36 fatcat:jiy74hd6knhtbd6ma33oacqmxi

Research on the Method of Feature-Based Multi-scale Vector Data Model [chapter]

Yibing Dong, Jianyu Yang, Chao Zhang, Dehai Zhu, Xingyue Tu, Xianzhe Qiao
2013 IFIP Advances in Information and Communication Technology  
Multi-scale representation of spatial data is a research focus in GIS, while building multi-scale data model is a key to implementing multi-scale representation of vector data.  ...  Finally, the object-oriented multi-scale logic model is researched, which lays a theoretical foundation for building the feature-based multi-scale vector data model.  ...  This research was funded by the National Natural Science Foundation Project "Research on Compression and Progressive Transmission of Vector Data in the Network Environment" (NO: 4171309).  ... 
doi:10.1007/978-3-642-36137-1_34 fatcat:xrh7zbgd4vbcvg4sf6dlzgytrq

Multi-level 3D CNN for Learning Multi-scale Spatial Features [article]

Sambit Ghadai, Xian Lee, Aditya Balu, Soumik Sarkar, Adarsh Krishnamurthy
2019 arXiv   pre-print
3D object recognition accuracy can be improved by learning the multi-scale spatial features from 3D spatial geometric representations of objects such as point clouds, 3D models, surfaces, and RGB-D data  ...  To demonstrate the utility of the proposed multi-level learning, we use a multi-level voxel representation of 3D objects to perform object recognition.  ...  This facilitates optimal learning from a multi-level data representation.  ... 
arXiv:1805.12254v2 fatcat:xfmichbn2jgn7gllu2uyknfkzu

Multi-Level 3D CNN for Learning Multi-Scale Spatial Features

Sambit Ghadai, Xian Yeow Lee, Aditya Balu, Soumik Sarkar, Adarsh Krishnamurthy
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
3D object recognition accuracy can be improved by learning the multi-scale spatial features from 3D spatial geometric representations of objects such as point clouds, 3D models, surfaces, and RGB-D data  ...  To demonstrate the utility of the proposed multi-level learning, we use a multi-level voxel representation of 3D objects to perform object recognition.  ...  In this paper, we present a novel approach to enable hierarchical learning of features from a flexible multi-level unstructured voxel representation of spatial data.  ... 
doi:10.1109/cvprw.2019.00150 dblp:conf/cvpr/GhadaiLBSK19 fatcat:qvqtpa47yjfl3mfixrl6lidd6y

Spatio-temporal and Multi-representation Modeling: A Contribution to Active Conceptual Modeling [chapter]

Stefano Spaccapietra, Christine Parent, Esteban Zimányi
2007 Lecture Notes in Computer Science  
Active conceptual modeling is a new framework intended to describe all aspects of a domain.  ...  This calls for a more accurate and complete understanding of underlying data, processes and events.  ...  It handles its four modeling dimensions -structural, spatial, temporal, and multi-representation -in a way that purposely makes the modeling dimensions orthogonal to each other (i.e., modeling in one dimension  ... 
doi:10.1007/978-3-540-77503-4_15 fatcat:gludrptks5gbpeixh4edf375ay

Remote sensing and social sensing data fusion for fine-resolution population mapping with a multi-model neural network

Luxiao Cheng, Lizhe Wang, Ruyi Feng, Jining Yan
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
This paper proposes a multi-model fusion neural network for estimating fine-resolution population estimates from multi-source data.  ...  We proposed a multi-model neural network, which combines a convolutional neural network (CNN) and a multilayer perceptron (MLP) model to estimate a fine-resolution population mapping.  ...  Furthermore, it introduces the representation method of spatial data and multi-model neural network in detail.  ... 
doi:10.1109/jstars.2021.3086139 fatcat:wn4lzpczqnalfgrut6ncmexqqu

Attention-Driven Body Pose Encoding for Human Activity Recognition [article]

B Debnath, M O'brien, S Kumar, A Behera
2020 arXiv   pre-print
The enriched data complements the 3D body joint position data and improves model performance.  ...  We also capture the contextual information from the RGB video stream using a Inception-ResNet-V2 model combined with a multi-head attention and a bidirectional Long Short-Term Memory (LSTM) network.  ...  The Spatial Encoding Unit (SEU) augments the spatial data with learned representations.  ... 
arXiv:2009.14326v2 fatcat:pbfnq5qsk5ajritj3apoz6cyiq

GAMA: A Spatially Explicit, Multi-level, Agent-Based Modeling and Simulation Platform [chapter]

Alexis Drogoul, Edouard Amouroux, Philippe Caillou, Benoit Gaudou, Arnaud Grignard, Nicolas Marilleau, Patrick Taillandier, Maroussia Vavasseur, Duc-An Vo, Jean-Daniel Zucker
2013 Lecture Notes in Computer Science  
The GAMA platform has been developed to address such issues and allow modelers, thanks to the use of a high-level modeling language, to build, couple and reuse complex models combining various agent architectures  ...  Agent-based modeling is now widely used to investigate complex systems but still lacks integrated and generic tools to support the representation of features usually associated with real complex systems  ...  In addition, GAMA manages the spatial projection of the data (to get a spatially coherent model) and the reading of attribute values.  ... 
doi:10.1007/978-3-642-38073-0_25 fatcat:okrbtoavmjbxfnw2se6foer46a

Multi-scale Octave Convolutions for Robust Speech Recognition [article]

Joanna Rownicka, Peter Bell, Steve Renals
2019 arXiv   pre-print
We propose a multi-scale octave convolution layer to learn robust speech representations efficiently.  ...  at two different spatial resolutions, one octave apart.  ...  Spatial average pooling in a low resolution group of feature maps can be interpreted as a form of low-pass filtering, providing smoothed representations of the observed data, potentially leading to improved  ... 
arXiv:1910.14443v1 fatcat:atfpyyw7dbfgda3swqzwthiidy

Modelling and Manipulating Multiple Representations of Spatial Data [chapter]

Christelle Vangenot, Christine Parent, Stefano Spaccapietra
2002 Advances in Spatial Data Handling  
One of the requirements which is poorly supported by spatial data models is a consistent management of different representations of the same spatial phenomena from different viewpoints or at different  ...  This paper proposes a conceptual data model providing full support for multiple representations of the same real world data.  ...  The Multi-Representation Framework MADS Data Model Our objective is to define a set of concepts necessary for describing datasets with multi-representation.  ... 
doi:10.1007/978-3-642-56094-1_7 fatcat:dcekwb57fzhq7hrjuj2ardvxkq

Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns

Ali Zonoozi, Jung-jae Kim, Xiao-Li Li, Gao Cong
2018 Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence  
explicit periodic representations, and can be optimized with multi-step ahead prediction.  ...  We observed recurring periodic patterns in some spatio-temporal data, which were not considered explicitly by previous non-linear works.  ...  ARIMA: ARIMA is a powerful linear model to fit and fore- cast time-series data.  ... 
doi:10.24963/ijcai.2018/519 dblp:conf/ijcai/ZonooziKLC18 fatcat:jithvapw3babtiqeym73znomxm

Theme section: Multi-dimensional modelling, analysis and visualization

Éric Guilbert, Arzu Çöltekin, Francesc Antón Castro, Chris Pettit
2016 ISPRS journal of photogrammetry and remote sensing (Print)  
(this issue), multi-spectral and multi-sensor data.  ...  Several issues need to be considered in order to provide a meaningful representation and assist in data visualisation and mining, modelling and analysis; such as data structures allowing representation  ...  We would like to thank all the authors who submitted a paper for this special issue and mostly our special thanks to the reviewers who contributed greatly through their constructive recommendations.  ... 
doi:10.1016/j.isprsjprs.2016.05.001 fatcat:aozmc6d3rnfbpjxgtmemycvyfy

Multi-granular Spatio-temporal Object Models: Concepts and Research Directions [chapter]

Elisa Bertino, Elena Camossi, Michela Bertolotto
2010 Lecture Notes in Computer Science  
In this paper we discuss how the modelling constructs of object data models can be extended for representing and querying multi-granular spatio-temporal objects.  ...  The capability of representing spatio-temporal objects is fundamental when analysing and monitoring the changes in the spatial configuration of a geographical area over a period of time.  ...  The representation of data at multiple levels of details, that is, at multiple granularities, is a topic of relevant interest also in modelling spatial entities.  ... 
doi:10.1007/978-3-642-14681-7_8 fatcat:7vgjz4y4znavjcz2xavao3il5a
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