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Automatic detection and evaluation of sugarcane planting rows in aerial images

Information Processing in Agriculture 2023年第3期10卷 400-415页

作者： Bruno Moraes Rocha Afonso Ueslei da Fonseca helio pedrini Fabrızzio Soares Instituto de Informa´tica Universidade Federal de Goia´sGoiaˆnia 74690-900GOBrazil Institute of Computing University of CampinasCampinas 13083-852SPBrazil

Sugarcane planting is an important and growing activity in ***,several techniques have been developed over the years to maximize crop productivity and profit,amongst them,processing of sugarcane field *** this sense,this research aims to identify and analyze crop rows and measure their gaps from aerial images of sugarcane *** this,a small Remotely Piloted Aircraft captured the images,generating orthomosaics of the areas for ***,each orthomosaic is classified with the K-Nearest Neighbor algorithm to segment regions of *** row orientation is estimated using the RGB gradient *** operations and computational geometry models are then used to detect and map rows and gaps along the planting row *** evaluate the results,crop rows are mapped and compared to manually taken *** technique obtained an error smaller than 2%when compared to gap length in crop rows from an orthomosaic with the area of 8.05 ha(ha).The proposed approach can map the positioning of the automatically generated row segments appropriately onto manually created ***,our method also achieved similar results when confronted with a manual technique for differing growth stages(40 and 80 days after harvest)of the sugarcane *** proposed method presents a great potential to be adopted in sugarcane planting monitoring。

关键词： Sugarcane Planting Rows Aerial Images Remotely Piloted Aircraft

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Multidimensional Projections for Visual Analysis of Social Networks

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Journal of Computer Science & Technology 2012年第4期27卷 791-810页

作者： Rafael Messias Martins Gabriel Faria Andery Henry Heberle Fernando Vieira Paulovich Alneu de Andrade Lopes helio pedrini Rosane Minghim Institute of Mathematics and Computer Science University of Sao PauloSao Carlos 13566-590Brazil CPM Braxis Capgemini Sao Paulo 04543-900Brazil Institute of Computing University of CampinasCampinas-SP 13083-852Brazil

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in atgribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

关键词： social network visual exploration multidimensional visualization

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Adaptive Lossy Image Compression Based on Singular Value Decomposition

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Journal of Signal and Information Processing 2019年第3期10卷 59-72页

作者： Marcos Roberto e Souza helio pedrini Institute of Computing University of Campinas Campinas SP Brazil

Image compression techniques aim to reduce redundant information in order to allow data storage and transmission in an efficient way. In this work, we propose and analyze a lossy image compression method based on the singular value decomposition using an optimal choice of eigenvalues and an adaptive mechanism for block partitioning. Experiments are conducted on several images to demonstrate the effectiveness of the proposed compression method in comparison with the direct application of the singular value decomposition.

关键词： Image Compression Adaptive Decomposition Lossy Compression

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NURBS Parameterization for Medical Surface Reconstruction

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Applied Mathematics 2016年第2期7卷 137-144页

作者： Dalton Fazanaro Paulo Amorim Thiago Moraes Jorge Silva helio pedrini Tridimensional Technology Division Center for Information Technology Renato Archer Campinas Brazil Institute of Computing University of Campinas Campinas Brazil

InVesalius is an open-source software for reconstruction of computed tomography and magnetic resonance images, which allows the user to make analysis and segmentation of virtual anatomical models. Physical models can be printed with the aid of rapid prototyping, giving the medical community a reliable instrument to help planning surgeries. To offer the user more control over the model, this work describes a methodology and tool developed for NURBS parameterization that provides mechanisms for adjusting the shape or even selecting a particular region of interest of the surface. Furthermore, the tool gives the option to export the final results of the process to a STEP file, which allows further edition in any well-known CAD software.

关键词： Parametric Modeling Surface Fitting B-Splines STEP File Export InVesalius

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Adaptive Lossy Image Compression Based on Singular Value Decomposition

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Journal of Signal and Information Processing（信号与信息处理） 2019年第3期

作者： Marcos Roberto e Souza helio pedrini

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