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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

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Novel hand biometric system using invariant descriptors

Novel hand biometric system using invariant descriptors

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international conference of Soft Computing and pattern recognition (SOCPAR)

作者： Nesrine Charfi Hanene Trichili Adel M. Alimi Basel Solaiman REGIM-Lab.: REsearch Groups in Intelligent Machines University of Sfax ENIS Sfax Tunisia Department of Image and Information Processing (ITI) Telecom-Bretagne (ENST) Brest France

Biometrics-based hand authentication is among the most popular biometrics used to automatically characterize a person especially in forensic applications. Hand recognition systems are able to confirm or deny the identity of a claimed person because they do not cause anxiety for the users. However, different individuals may have almost similar hands. therefore, the performance of the hand verification process depends highly on the hand descriptors. In this paper, we propose a new approach for personal verification based on Scale Invariant Feature Transform (SIFT). this transform proved its high distinction and efficiency in many applications especially in object recognition and video tracking. Two public databases have been used to evaluate performances. Experimental results show promising recognition rates by achieving 94% for IITD hand database and 98% for Bosphorus hand database.

关键词： Feature extraction Databases Shape Transforms pattern recognition Biometrics (access control) Principal component analysis

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Building test collection from Old IR literature 14

Building test collection from Old IR literature

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6th international Workshop of the Forum for Information Retrieval Evaluation, FIRE 2014

作者： Chakraborty, Anirban Ghosh, Kripabandhu Parui, Swapan Kumar Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India

ISBN: (纸本)9781450337557

Standard test collections form the very basis of Information Retrieval research and evaluation. Important datasets have been created to promote empirical research and experimentation. In this paper, we describe our endeavour in creating a test collection from old, archived writings of IR stalwarts. the documents are created in text format from the scanned and OCRed version. the test collection consists of a set of documents in TREC format along with a set of expert queries and their relevance assessments. this dataset, though small in size, would be of paramount interest for researchers and students of IR since it contains valuable discourses on the discipline from its very inception. Also, to the best of our knowledge, no standard IR dataset has been built so far comprising old research articles. Furthermore, this is a dataset without the original error-free digital text version. So, the resulting collection would expect researchers to run retrieval experiments on the erroneous collection without the scope of error modeling. this would invite new research ideas. © 2015 ACM.

关键词： Errors

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Multi-modal supervised latent dirichlet allocation for event classification in social media 14

Multi-modal supervised latent dirichlet allocation for event...

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6th international conference on Internet Multimedia Computing and Service, ICIMCS 2014

作者： Qian, Shengsheng Zhang, Tianzhu Xu, Changsheng National Lab of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781450328104

In social media, many existing websites (e.g., Flickr, YouTube, and Facebook) are for users to share their own interests and opinions of many popular events, and success-fully facilitate the event generation, sharing and propagation. As a result, there are substantial amounts of user-contributed media data (e.g., images, videos, and textual content) for a wide variety of real-world events of different types and scales. the aim of this paper is to automatically identify the interesting events from massive social media data, which are useful to browse, search and monitor social events by users or governments. To achieve this goal, we propose a novel multi-modal supervised latent dirichlet allocation (mm-SLDA) for social event classification. Our proposed mm-SLDA has a number of advantages. (1) It can effectively exploit the multi-modality and the multi-class property of social events jointly. (2) It makes use of the supervised social event category label information and is able to classify multi-class social event directly. We evaluate our proposed mm-SLDA on a real world dataset and show extensive experimental results, which demonstrate that our model outperforms state-of-the-art methods. Copyright 2014 ACM.

关键词： Classification (of information)

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A modified hybrid naïve possibilistic Classifier for heart disease detection from heterogeneous medical data

A modified hybrid naïve possibilistic Classifier for heart ...

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international conference of Soft Computing and pattern recognition (SOCPAR)

作者： Karim Baati Tarek M. Hamdani Adel M. Alimi University of Monastir Higher Institute of Computer Science of Mahdia Tunisia REGIM-Lab.: REsearch Groups on Intelligent Machines University of Sfax. National Engineering School of Sfax (ENIS) Sfax. Tunisia College of Science And arts at AI-Ula Taibah University al-Madinah al-Munawwarah KSA

In this paper, we propose a modified Hybrid Naïve Possibilistic Classifier (HNPC) for heart disease detection from the heterogeneous data (numerical and categorical) of the Cleveland dataset. the proposed classifier is based on a different pattern with regard to our former HNPC which have been recently proposed to deal with the same problem. As HNPC, the modified classifier separates data into two subsets (numerical and categorical) and then estimates possibility beliefs using the two versions of the probability-possibility transformation method of Dubois ets al. for numerical and categorical data, respectively. However, unlike HNPC which is based on two fusion steps to make decision from possibility estimations, our new classifier performs a common fusion to combine these beliefs. During this fusion, the product and the minimum as main combination operators for possibility measures are investigated. Experimental evaluations on the Cleveland dataset show that the proposed modified HNPC may outperform the former HNPC as well as the main classification techniques which have been used in recent related work.

关键词： Diseases Heart Possibility theory Data models Educational institutions conferences pattern recognition

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A case study on the analysis of behavior patterns and pattern changes in smart environments

A case study on the analysis of behavior patterns and patter...

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6th international Work-conference on Ambient Assisted Living, IWAAL 2014

作者： Lago, Paula Jiménez-Guarín, Claudia Roncancio, Claudia Systems and Computing Engineering Department School of Engineering Universidad de los Andes Colombia Univ. Grenoble Alpes LIG France

ISBN: (纸本)9783319131047

Societies need to devise mechanisms of caring for the well aging of the increasing number of seniors, as it is very important for elderly people to maintain their independence. Smart environments are being devised as a form of care in what has been called ambient assisted living. A smart environment should be able to respond in case of emergency or risk and inform any abnormal behavior. Still, not much research is done to understand behavior patterns, temporal changes and other particularities that can affect the effectiveness of smart environments in ambient assisted living. We explored the behavior of two adults in a smart environment in order to reveal temporal, spatial and sequential relations among the activities as well as the changes that these relations undergo overtime and across individuals. this paper presents an analysis of three human behavior patterns: temporal, location and frequency. these patterns are mined on two experimental subjects using the dataset provided by the CASAS project. Our analysis evidences how temporal, spatial and sequential patterns differ from person to person, day to day and after some time. Learning personalized behaviors and identifying and adapting to changes is a crucial aspect for smart environments since one-fit-all solutions are not suitable. © Springer international Publishing Switzerland 2014.

关键词： Assisted living

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pattern recognition in bioinformatics - 7th iapr international conference, PRIB 2012, Proceedings

Pattern Recognition in Bioinformatics - 7th IAPR Internation...

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7th iapr international conference on pattern recognition in bioinformatics, PRIB 2012

ISBN: (纸本)9783642341229

the proceedings contain 24 papers. the topics discussed include: robust community detection methods with resolution parameter for complex detection in protein-protein interaction networks;machine learning scoring functions based on random forest and support vector regression;multiple tree alignment with weights applied to carbohydrates to extract binding recognition patterns;improving the portability and performance of *** - a dynamic RNA visualization software;a novel machine learning approach for detecting the brain abnormalities from MRI structural images;an algorithm to assemble gene-protein-reaction associations for genome-scale metabolic model reconstruction;a machine learning and chemometrics assisted interpretation of spectroscopic data - a NMR-based metabolomics platform for the assessment of Brazilian Propolis;and application of the multi-modal relevance vector machine to the problem of protein secondary structure prediction.

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Performance Improvement of Face recognition Algorithms Using Occluded-Region Detection

Performance Improvement of Face Recognition Algorithms Using...

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6th iapr international conference on Biometrics (ICB)

作者： Tajima, Yuichiro Ito, Koichi Aoki, Takafumi Hosoi, Tomoki Nagashima, Sei Kobayashi, Koji Tohoku Univ Grad Sch Informat Sci 6-6-05 Aramaki Aza Aoba Sendai Miyagi 9808579 Japan Azbil Corp Fujisawa Kanagawa 251852 Japan

ISBN: (纸本)9781479903108

Facial occlusions such as eyeglasses, hairs and beards decrease the performance of face recognition algorithms. To improve the performance of face recognition algorithms, this paper proposes a novel framework of face recognition combined with the occluded-region detection method. In this paper, we detect occluded regions using Fast-Weighted Principal Component Analysis (FW- PCA) and use the occluded regions as weights for matching face images. To demonstrate the effectiveness of the proposed framework, we use two face recognition algorithms: Local Binary patterns (LBP) and Phase-Only Correlation (POC). Experimental evaluation using public face image databases indicates performance improvement of the face recognition algorithms for face images with natural and artificial occlusions.

关键词： Local binary pattern

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Deformed Iris recognition Using Bandpass Geometric Features and Lowpass Ordinal Features

Deformed Iris Recognition Using Bandpass Geometric Features ...

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6th iapr international conference on Biometrics (ICB)

作者： Zhang, Man Sun, Zhenan Tan, Tieniu Chinese Acad Sci Natl Lab Pattern Recognit Inst Automat Ctr Res Intelligent Percept & Comp Beijing 100190 Peoples R China

ISBN: (纸本)9781479903108

Deformation of iris pattern caused by pupil dilation and contraction is one of the most influential intra-class variations. Most state-of-the-art iris recognition methods only focus on the description of local iris texture features. We believe that both geometric and photometric features are important to achieve a robust matching result of deformed iris images. this paper proposes to decompose iris images into lowpass and bandpass components using nonsubsampled contourlet transform (NSCT) and then extract different features. Geometric features are extracted in bandpass components based on key point detection to align deformed iris patterns. And then aligned Ordinal features are extracted in lowpass components to characterize the ordinal measures of local iris regions. Finally, key point features in bandpass components and Ordinal features in lowpass components are fused for deformed iris image matching. Extensive experiments on two challenging iris image databases namely CASIA-Iris-Lamp and ICE'2005 demonstrate that the proposed method outperforms state-of-the-art methods in deformed iris recognition.

关键词： Geometry

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DNA Sequence recognition Based on the Markov Model

DNA Sequence Recognition Based on the Markov Model

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6th international conference on Biomedical Engineering and Informatics (BMEI)

作者： Zhang, Junyan Yang, Chenhui Chengdu Univ Informat Sci & Technol Coll Chengdu Peoples R China Chengdu Univ Key Lab Pattern Recognit & Intelligent Informat P Chengdu Peoples R China

ISBN: (纸本)9781479927616

DNA sequences recognition is a key problem in bioinformatics and biomedical informatics. In this paper, we solve this problem by use of the probability method and metric instead of traditional frequency metric because the characters in DNA alphabet set meet the Markov properties. For this purpose, transition probabilities, transition matrixes, and log odds ratios are defined. And then, we put forward our sequence recognition algorithm based on the Markov model (SRM), which has better performance on time complexity than some sequence alignment algorithms in the same field. the results of the contrast experiments show that our SRM algorithm can recognize DNA sequences correctly and effectively without any ambiguities.

关键词： DNA sequence recognition Markov model

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Optimizing Cache Locality for Irregular Data Accesses on Many-Core Intel Xeon Phi Accelerator Chip

Optimizing Cache Locality for Irregular Data Accesses on Man...

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IEEE international conference on High Performance Computing and Communications (HPCC)

作者： Nhat Phuong Tran Dong Hoon Choi Myungho Lee Department of Computer Science and Engineering Myongji University Cheo-In Gu Yong In Kyung Ki Do Korea Korea Institute of Science and Technology Information (KISTI) Yuseong-Gu Daejeon Korea

ISBN: (纸本)9781479961245

Many-core accelerator chips are becoming increasingly popular these days for its high performance floating-point performance exceeding 1 Tflops per chip. Aho-Corasick (AC) is a multiple patterns string matching algorithm commonly used in computer and network security, bioinformatics, among others. In order to simultaneously match a number of string patterns with respect to the input text data, a Deterministic Finite Automata (DFA) is constructed from a given set of pattern strings. the DFA is referenced almost randomly, whereas the input data is sequentially accessed. As the number of pattern strings increases, the irregular DFA accesses lead to poor cache locality and low overall performance. In this paper, we present a cache locality optimizing parallelization on the many-core accelerator chip, the Intel Xeon Phi. A given set of pattern strings is partitioned into into multiple sets of a smaller number of patterns so that multiple small DFAs are constructed instead of single large DFA. the accesses to multiple small DFAs lead to significantly smaller cache footprints in each core's cache and result in impressive performance improvements. Experimental results on the Intel Xeon Phi 5110P show that our approach delivers up to 2.00 × speedup compared with the previous approach using single large DFA.

关键词： pattern matching Graphics processing units Coprocessors Automata Computer architecture Partitioning algorithms

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