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检索条件"任意字段=12th International Conference on Computing and Pattern Recognition, ICCPR 2023"

共 284 条记录，以下是141-150 订阅

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A Wireless Body Sensor Network For Activity Monitoring With Low Transmission Overhead 12

A Wireless Body Sensor Network For Activity Monitoring With ...

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12th IEEE/IFIP international conference on Embedded and Ubiquitous computing (EUC)

作者： Braojos, Ruben Beretta, Ivan Constantin, Jeremy Burg, Andreas Atienza, David Ecole Polytech Fed Lausanne Embedded Syst Lab CH-1015 Lausanne Switzerland Ecole Polytech Fed Lausanne Telecommun Circuits Lab CH-1015 Lausanne Switzerland

ISBN: (纸本)9780769552491

Activity recognition has been a research field of high interest over the last years, and it finds application in the medical domain, as well as personal healthcare monitoring during daily home-and sports-activities. With the aim of producing minimum discomfort while performing supervision of subjects, miniaturized networks of low-power wireless nodes are typically deployed on the body to gather and transmit physiological data, thus forming a Wireless Body Sensor Network (WBSN). In this work, we propose a WBSN for online activity monitoring, which combines the sensing capabilities of wearable nodes and the high computational resources of modern smartphones. the proposed solution provides different tradeoffs between classification accuracy and energy consumption, thanks to different workloads assigned to the nodes and to the mobile phone in different network configurations. In particular, our WBSN is able to achieve very high activity recognition accuracies (up to 97.2%) on multiple subjects, while significantly reducing the sampling frequency and the volume of transmitted data with respect to other state-of-the-art solutions.

关键词： body sensor networks computerised instrumentation energy consumption fuzzy neural nets mobile computing mobile handsets pattern classification WBSN activity monitoring activity recognition accuracies classification accuracy mobile phone neuro-fuzzy classifier sampling frequency smartphones transmission overhead wearable nodes wireless body sensor network Accuracy Biomedical monitoring Feature extraction Monitoring Smart phones Wireless communication Wireless sensor networks Body sensor networks Smartphone Mobile phones Fuzzy neural networks energy consumption computerised instrumentation Biomedical monitoring CARRIER SYSTEM pattern recognition Mobile computing Feature extraction Wireless sensor networks SAMPLING FREQUENCY

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Fixed-lag particle filter for continuous context discovery using Indian Buffet Process

Fixed-lag particle filter for continuous context discovery u...

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2014 12th IEEE international conference on Pervasive computing and Communications, PerCom 2014

作者： Nguyen, thuong Gupta, Sunil Venkatesh, Svetha Phung, Dinh Centre for Pattern Recognition and Data Analytics Deakin University Australia

ISBN: (纸本)9781479934454

Exploiting context from stream data in pervasive environments remains a challenge. We aim to extract proximal context from Bluetooth stream data, using an incremental, Bayesian nonparametric framework that estimates the number of contexts automatically. Unlike current approaches that can only provide final proximal grouping, our method provides proximal grouping and membership of users over time. Additionally, it provides an efficient online inference. We construct co-location matrix over time using Bluetooth data. A Poisson-exponential model is used to factorize this matrix into a factor matrix, interpreted as proximal groups, and a coefficient matrix that indicates factor usage. the coefficient matrix follows the Indian Buffet Process prior, which estimates the number of factors automatically. the non-negativity and sparsity of factors are enforced by using the exponential distribution to generate the factors. We propose a fixed-lag particle filter algorithm to process data incrementally. We compare the incremental inference (particle filter) with full batch inference (Gibbs sampling) in terms of normalized factorization error and execution time. the normalized error obtained through our incremental inference is comparable to that of full batch inference, whilst the execution time is more than 100 times faster. the discovered factors have similar meaning to the results of the popular Louvain method for community detection. © 2014 IEEE.

关键词： Bluetooth

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GPU-Based Fast Training of Discriminative Learning Quadratic Discriminant Function for Handwritten Chinese Character recognition

GPU-Based Fast Training of Discriminative Learning Quadratic...

引用

12th international conference on Document Analysis and recognition (ICDAR)

作者： Zhou, Ming-Ke Yin, Fei Liu, Cheng-Lin Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

ISBN: (纸本)9781479901937

the discriminative training of classifiers for handwritten Chinese character recognition (HCCR) is highly demanding in computation due to the large number of categories. the inability of discriminative training with large sample set on personal computers has hindered the accuracy promotion for HCCR. To overcome this problem, we have implemented the training algorithm of discriminative learning quadratic discriminant function (DLQDF) on our graphics processing units (GPU) server, and have achieved 15 times speedup compared to single-core computation. By enlarging training sample set via distortion on a standard dataset of 3,755 classes, we could train the DLQDF on more than 50 million samples within 150min and get the test accuracy improved by 1.36%.

关键词： handwritten Chinese character recognition discriminative learning modified quadratic discriminant function GPU parallel computing sample synthesis

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ICDAR 2013 CROHME: third international Competition on recognition of Online Handwritten Mathematical Expressions

ICDAR 2013 CROHME: Third International Competition on Recogn...

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12th international conference on Document Analysis and recognition (ICDAR)

作者： Mouchere, Harold Viard-Gaudin, Christian Zanibbi, Richard Garain, Utpal Kim, Dae Hwan Kim, Jin Hyung Univ Nantes Ecole Polytech LUNAM IRCCyN IVC UMR CNRS 6597 F-44306 Nantes 03 France Rochester Inst Technol Dept Comp Sci Rochester NY 14623 USA Indian Stat Inst Comp Vision & Pattern Recognit Unit Kolkata India Korea Adv Inst Sci & Technol Taejon 305701 South Korea

We report on the third international Competition on Handwritten Mathematical Expression recognition (CROHME), in which eight teams from academia and industry took part. For the third CROHME, the training dataset was expanded to over 8000 expressions, and new tools were developed for evaluating performance at the level of strokes as well as expressions and symbols. As an informal measure of progress, the performance of the participating systems on the CROHME 2012 data set is also reported. Data and tools used for the competition will be made publicly available.

关键词： handwritten character recognition mathematics computing

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Two-Dimensional Hidden Markov Models for pattern recognition

Two-Dimensional Hidden Markov Models for Pattern Recognition

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12th international conference on Artificial Intelligence and Soft computing, ICAISC 2013

作者： Bobulski, Janusz Adrjanowicz, Lukasz Czestochowa Tech Univ Inst Comp & Informat Sci PL-42200 Czestochowa Poland

ISBN: (纸本)9783642386572

Hidden Markov models are well-known methods for image processing. they are used in many areas where 1D data are processed. In the case of 2D data, there appear some problems with application HMM. there are some solutions, but they convert input observation from 2D to 1D, or create parallel pseudo 2D HMM, which is set of 1D HMMs in fact. this paper describes authentic 2D HMM with two-dimensional input data, and its application for pattern recognition in image processing.

关键词： hidden Markov model pattern recognition image processing

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Functional mesh learning for pattern analysis of cognitive processes

Functional mesh learning for pattern analysis of cognitive p...

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12th IEEE international conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2013

作者： Firat, Orhan Özay, Mete Önal, Itir Oztekin, Ilke Vural, Fatoş T. Yarman Department of Computer Engineering Middle East Technical University Ankara Turkey Department of Psychology Koç University Istanbul Turkey

ISBN: (纸本)9781479907816

We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resonance imaging (fMRI). In the proposed learning machine, local meshes are formed around each voxel. the distance between voxels in the mesh is determined by using functional neighborhood concept. In order to define functional neighborhood, the similarities between the time series recorded for voxels are measured and functional connectivity matrices are constructed. then, the local mesh for each voxel is formed by including the functionally closest neighboring voxels in the mesh. the relationship between the voxels within a mesh is estimated by using a linear regression model. these relationship vectors, called Functional Connectivity aware Local Relational Features (FC-LRF) are then used to train a statistical learning machine. the proposed method was tested on a recognition memory experiment, including data pertaining to encoding and retrieval of words belonging to ten different semantic categories. Two popular classifiers, namely k-Nearest Neighbor and Support Vector Machine, are trained in order to predict the semantic category of the item being retrieved, based on activation patterns during encoding. the classification performance of the Functional Mesh Learning model, which range in 62-68% is superior to the classical multi-voxel pattern analysis (MVPA) methods, which range in 40-48%, for ten semantic categories. © 2013 IEEE.

关键词： Encoding (symbols)

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moviQuest-MAS: An Intelligent Platform for Ubiquitous Social Networking Business

moviQuest-MAS: An Intelligent Platform for Ubiquitous Social...

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12th international conference on Artificial Intelligence and Soft computing, ICAISC 2013

作者： Soto, Ramon Soto, Alexandro Camalich, Juan Univ Sonora Dept Accounting Hermosillo Sonora Mexico Univ Sonora Dept Math Hermosillo Sonora Mexico SA CV Dept Engn moviQuest Hermosillo Sonora Mexico

ISBN: (纸本)9783642386091

New communications technologies have revolutionized human interaction. One of the main features of this new order is an explosion of relationships a person can establish and the issues that she can start. However, keeping control of the course of these relationships has become a very complex issue. this paper presents a generic platform for implementing social networks which aim to establish serious relationships between people based on their membership to affinity groups. the proposed social network platform uses an artificial intelligence approach which has been designated as Ubiquitous Artificial Intelligence. the basis of this approach is a multi-agent architecture that integrates a variety of pattern recognition algorithms to determine the profiles of social network use along with mobile expert systems that assist the user in their social network communication from the mobile. this approach also uses a specific ontology of the social network that simplifies communication and makes it safer.

关键词： Social networks Mobile computing Intelligent computing Multiagent technologies

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ICDAR 2013 Competition on Historical Book recognition (HBR 2013)

ICDAR 2013 Competition on Historical Book Recognition (HBR 2...

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international conference on Document Analysis and recognition

作者： A. Antonacopoulos C. Clausner C. Papadopoulos S. Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Manchester UK

this paper presents an objective comparative evaluation of layout analysis and recognition methods for scanned historical books. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2013 and the 2nd international Workshop on Historical Document Imaging and Processing (HIP2013), presenting the results of the evaluation of five methods - three submitted and two state-of-the-art systems (one commercial and one open-source). three scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions, one evaluating segmentation and region classification (with a text extraction goal) and the other the whole pipeline including recognition. the results indicate that there is a convergence to a certain methodology, in terms of layout analysis, with some variations in the approach. However, there is still a considerable need to develop robust methods that deal with the idiosyncrasies of historical books, especially for OCR.

关键词： Layout Optical character recognition software Particle separators Performance evaluation Video recording Text analysis Image segmentation

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the Significance of Reading Order in Document recognition and Its Evaluation

The Significance of Reading Order in Document Recognition an...

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international conference on Document Analysis and recognition

作者： C. Clausner S. Pletschacher A. Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Manchester UK

ISBN: (纸本)9781479901937

Reading order detection and representation is an important task in many digitisation scenarios involving the preservation of the logical structure of a document. the corresponding need for the evaluation of reading order results generated by layout analysis methods poses a particular challenge due to potential deviations between ground truth and actually detected segmentation of the page. To this end a novel evaluation approach that responds to this problem by incorporating region correspondence analysis is proposed. Furthermore, a sophisticated reading order representation scheme is presented and used by the system allowing the grouping of objects with ordered and/or unordered relations. this is a typical requirement for documents with complex layouts such as magazines and newspapers. the evaluation method has been validated using the results of two state-of-the-art OCR / layout analysis systems and a basic top-to-bottom reading order detection algorithm applied on representative samples from the PRImA contemporary and the IMPACT historical document datasets.

关键词： Layout Text analysis Optical character recognition software Performance evaluation Text recognition Engines

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ICDAR 2013 Competition on Historical Newspaper Layout Analysis (HNLA 2013)

ICDAR 2013 Competition on Historical Newspaper Layout Analys...

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international conference on Document Analysis and recognition

this paper presents an objective comparative evaluation of layout analysis methods for scanned historical newspapers. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2013 and the 2nd international Workshop on Historical Document Imaging and Processing (HIP2013), presenting the results of the evaluation of five submitted methods. Two state-of-the-art systems, one commercial and one open-source, are also evaluated for comparison. Two scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions and the other evaluating the whole pipeline of segmentation and region classification (with a text extraction goal). the results indicate that there is a convergence to a certain methodology with some variations in the approach. However, there is still a considerable need to develop robust methods that deal with the idiosyncrasies of historical newspapers.

关键词： Layout Particle separators Image segmentation Performance evaluation Video recording Text analysis Image analysis

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