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检索条件"任意字段=5th International Workshop on Graph-Based Representations in Pattern Recognition"

共 194 条记录，以下是61-70 订阅

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Report on the first contest on graph matching algorithms for pattern search in biological databases 10

Report on the first contest on graph matching algorithms for...

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10th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2015

作者： Carletti, Vincenzo Foggia, Pasquale Vento, Mario Jiang, Xiaoyi Department of Information Engineering Electrical Engineering and Applied Mathematics University of Salerno Fisciano Italy Department of Computer Science University of Münster Münster Germany

ISBN: (纸本)9783319182230

graphs are a powerful data structure that can be applied to several problems in bioinformatics, and efficient graph matching is often a tool required for several applications that try to extract useful information from large databases of graphs. While graph matching is in general a NP-complete problem, several algorithms exist that can be fast enough on practical graphs. However, there is no single algorithm that is able to outperform the others on every kind of graphs, and so it is of paramount importance to assess the algorithms on graphs coming from the actual problem domain. To this aim, we have organized the first edition of the Contest on graph Matching Algorithms for pattern Search in Biological Databases, hosted by the ICPR2014 Conference, so as to provide an opportunity for comparing state-of-the-art matching algorithms on a new graph database built using several kinds of real-world graphs found in bioinformatics applications. the participating algorithms were evaluated with respect to both their computation time and their memory usage. this paper will describe the contest task and databases, will provide a brief outline of the participating algorithms, and will present the results of the contest. © Springer international Publishing Switzerland 2015.

关键词： Bioinformatics

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A subpath kernel for learning hierarchical image representations 10

A subpath kernel for learning hierarchical image representat...

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10th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2015

作者： Cui, Yanwei Chapel, Laetitia Lefèvre, Sébastien University Bretagne-Sud Vannes56000 France

ISBN: (纸本)9783319182230

Tree kernels have demonstrated their ability to deal with hierarchical data, as the intrinsic tree structure often plays a discriminative role. While such kernels have been successfully applied to various domains such as nature language processing and bioinformatics, they mostly concentrate on ordered trees and whose nodes are described by symbolic data. Meanwhile, hierarchical representations have gained increasing interest to describe image content. this is particularly true in remote sensing, where such representations allow for revealing different objects of interest at various scales through a tree structure. However, the induced trees are unordered and the nodes are equipped with numerical features. In this paper, we propose a new structured kernel for hierarchical image representations which is built on the concept of subpath kernel. Experimental results on both artificial and remote sensing datasets show that the proposed kernel manages to deal with the hierarchical nature of the data, leading to better classification rates. © Springer international Publishing Switzerland 2015.

关键词： Image classification

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5th international Provenance and Annotation workshop, IPAW 2014

5th International Provenance and Annotation Workshop, IPAW 2...

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5th international Provenance and Annotation workshop, IPAW 2014

ISBN: (纸本)9783319164618

the proceedings contain 45 papers. the special focus in this conference is on Standardization of Provenance Models, Services, representations, Applications of Provenance, Provenance Management Architectures, Security and Privacy Implications of Provenance. the topics include: Generating synthetic PROV graphs with predictable structure;walking into the future with PROV pingback;regenerating and quantifying quality of benchmarking data using static and dynamic provenance;capturing and analyzing provenance of scripts;exploiting workflow provenance to surface scientific data provenance;auditing and maintaining provenance in software packages;a provenance-based policy control framework for cloud services;applying provenance to protect attribution in distributed computational scientific experiments;generating scientific documentation for computational experiments using provenance;computing location-based lineage from workflow specifications to optimize provenance queries;a lightweight provenance pingback and query service for web publications;provenance-based searching and ranking for scientific workflows;improving workflow design using abstract provenance graphs;early discovery of tomato foliage diseases based on data provenance and pattern recognition;enhancing provenance representation with knowledge based on NFR conceptual modeling;towards supporting provenance gathering and querying in different database approaches;challenges for provenance analytics over geospatial data;using well-founded provenance ontologies to query meteorological data and provenance support for medical research.

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Early Discovery of Tomato Foliage Diseases based on Data Provenance and pattern recognition 5

Early Discovery of Tomato Foliage Diseases Based on Data Pro...

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5th international Provenance and Annotation workshop (IPAW)

作者： Nunes, Diogo Werly, Carlos Vianna, Gizelle Kupac Serra da Cruz, Sergio Manuel UFRRJ Seropedica RJ Brazil UFRRJ PPGMMC Seropedica RJ Brazil UFRRJ PET SI Seropedica RJ Brazil

ISBN: (纸本)9783319164625;9783319164618

this work presents an approach focused in enhancing the quality of tomato crops. We are developing and using low cost computational strategies to support early detection of the late blight. Our approach consorts tomatoes cultivars in an experimental field with inexpensive computer-aided resources based on Web and Android mobile tools in which workers collect scouting data and annotations and take images about the state of the crop, and in image filtering techniques and pattern recognition to detect foliage diseases on tomatoes images. In this study, we use provenance metadata about field observations, images and farmers' annotations as well, to improve the efficiency and accuracy of the patterns recognition algorithms. Our identification method achieved a hit rate of 94.12 %, using a reduced set of digital images of the tomato crops.

关键词： Provenance pattern recognition Neural networks

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Long short term memory recurrent neural network based multimodal dimensional emotion recognition 5

Long short term memory recurrent neural network based multim...

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5th international workshop on Audio/Visual Emotion Challenge, AVEC 2015 - co-Located with MM 2015

作者： Chao, Linlin Tao, Jianhua Yang, Minghao Li, Ya Wen, Zhengqi National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781450337434

this paper presents our effort to the Audio/Visual+ Emotion Challenge (AV+EC2015), whose goal is to predict the continuous values of the emotion dimensions arousal and valence from audio, visual and physiology modalities. the state of art classifier for dimensional recognition, long short term memory recurrent neural network (LSTM-RNN) is utilized. Except regular LSTM-RNN prediction architecture, two techniques are investigated for dimensional emotion recognition problem. the first one is Ε- insensitive loss is utilized as the loss function to optimize. Compared to squared loss function, which is the most widely used loss function for dimension emotion recognition, Ε-insensitive loss is more robust for the label noises and it can ignore small errors to get stronger correlation between predictions and labels. the other one is temporal pooling. this technique enables temporal modeling in the input features and increases the diversity of the features fed into the forward prediction architecture. Experiments results show the efficiency of key points of the proposed method and competitive results are obtained. © 2015 ACM.

关键词： Emotion recognition

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5th international workshop on Computational Color Imaging, CCIW 2015

5th International Workshop on Computational Color Imaging, C...

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5th international workshop on Computational Color Imaging, CCIW 2015

ISBN: (纸本)9783319159782

the proceedings contain 23 papers. the special focus in this conference is on Color reproduction, Color sensation and perception, Color image processing, Spectral imaging and Color in digital cultural heritage. the topics include: Color and spectral mixings in printed surfaces;an overview of color name applications in computer vision;optics and computational methods for hybrid resolution spectral imaging;relative pose estimation and fusion of 2D spectral and 3D lidar images;representation of cultural objects by image sets with directional illumination;descriptor-based image colorization and regularization;experimental analysis for modeling color of halftone images;development of a dynamic relighting system for moving planar objects with unknown reflectance;collection, analysis and representation of memory color information;the display gamut available to simulate colors perceived by anomalous trichromats;visual search for normal color and dichromatic observers using a unique distracter color;first stage of a human visual system simulator;the color logarithmic image processing (CoLIP) antagonist space and chromaticity diagram;does color influence image complexity perception?;adaptive filters for color images: median filtering and its extensions;can linear data projection improve hyperspectral face recognition?;spectral impulse noise model for spectral image processing;evaluation of the colorimetric performance of single-sensor image acquisition systems employing colour and multispectral filter array;high-resolution multispectral scanning for mesoscopic investigation of discoloration of traditional Japanese pigments and estimating the colors of paintings.

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Human Gait recognition: Viewing Angle Effect on Normal Walking pattern 5

Human Gait Recognition: Viewing Angle Effect on Normal Walki...

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5th international Conference on Computer and Communication Engineering (ICCCE 2014)

作者： Makhdoomi, Nahid A. Gunawaan, Teddy S. Habaebi, Mohamed H. Ab Rahim, Rosminazuin Int Islamic Univ Malaysia Fac Engn Dept Elect & Comp Engn Kuala Lumpur Malaysia

ISBN: (纸本)9781479976355

Gait recognition has recently gained interest of researchers as it performs identification of subjects at a distance from the camera. However, due to the changes in the viewing angles, it gets cumbersome for a system to perform recognition based on the walking pattern of an individual. In this work, the aim is to propose a simple baseline method for the purpose of human recognition based on the shape of its body and walking pattern when the subject is observed from different viewing angles. the recognition is also tested on the subjects in a scenario where the individual subjects are registered while walking in normal walking pattern followed by the testing in normal walking mode, apart from being observed at different viewing angles. Gait periodicity is estimated after extracting the silhouettes of an individual, followed by obtaining the total silhouette representation of an individual using Matlab. the total silhouette representations obtained from the probe gait data are compared to the gallery gait data representations for the purpose of similarity computation by calculating the RMS value between the said representations. Higher the value, lesser is the similarity & vice versa.

关键词： gait recognition biometrics identification gait-database

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A Robust Approach to Extraction of Texts from Camera Captured Images

A Robust Approach to Extraction of Texts from Camera Capture...

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5th international workshop on Camera-based Document Analysis and recognition (CBDAR)

作者： Banerjee, Sudipto Mullick, Koustav Bhattacharya, Ujjwal Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata India Heritage Inst Technol Dept Comp Sci & Engn Kolkata India

ISBN: (纸本)9783319051673;9783319051666

Here, we present our recent study of a robust but simple approach to extraction of texts from camera-captured images. In the proposed approach, we first identify pixels which are highly specular. Connected components of this set of specular pixels are obtained. Pixels belonging to each such component are separately binarized using the well-known Otsu's approach. We next apply smoothing on the whole image before obtaining its Canny edge representation. Bounding rectangle of each connected component of the Canny edge image is obtained and multiple components with pairwise overlapping bounding boxes are merged. Otsu's thresholding technique is applied separately on different parts of input image defined by the resulting bounding boxes. Although Otsu's thresholding approach does not generally provide acceptable performance on camera captured images, we observed its suitability when applied severally as in the above. the binarized specular components obtained at the initial stage replace the corresponding regions of the latter binarized image. Finally, a set of postprocessing operations is used to remove certain non-text components of the binarized image.

关键词： Pixels

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A comparison of explicit and implicit graph embedding methods for pattern recognition

A comparison of explicit and implicit graph embedding method...

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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

作者： Conte, Donatello Ramel, Jean-Yves Sidère, Nicolas Luqman, Muhammad Muzzamil Gaüzère, Benoît Gibert, Jaume Brun, Luc Vento, Mario Italy 64 Avenue Jean Portalis 37200 Tours France L3i Laboratory University of la Rochelle 17042 La Rochelle France GREYC UMR CNRS 6072 14000 Caen France

ISBN: (纸本)9783642382208

In recent years graph embedding has emerged as a promising solution for enabling the expressive, convenient, powerful but computational expensive graph based representations to benefit from mature, less expensive and efficient state of the art machine learning models of statistical pattern recognition. In this paper we present a comparison of two implicit and three explicit state of the art graph embedding methodologies. Our preliminary experimentation on different chemoinformatics datasets illustrates that the two implicit and three explicit graph embedding approaches obtain competitive performance for the problem of graph classification. © 2013 Springer-Verlag.

关键词： Classification (of information)

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On the evaluation of graph centrality for shape matching

On the evaluation of graph centrality for shape matching

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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

作者： De Sousa, Samuel Artner, Nicole M. Kropatsch, Walter G. Vienna University of Technology Pattern Recognition and Image Processing Group Vienna Austria

ISBN: (纸本)9783642382208

graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the Shape Matching task. We create a graph-based representation of a shape and describe this graph by using different centrality measures. We build a Naive Bayes classifier whose input feature vector consists of the measurements obtained by the centralities and evaluate the different performances for each centrality. © 2013 Springer-Verlag.

关键词： graphic methods

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