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Isolated Handwritten Malayalam Character recognition Using HLH Intensity patterns

Isolated Handwritten Malayalam Character Recognition Using H...

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international conference on Machine Learning and computing

作者： M. Abdul Rahiman Aswathy Shajan Amala Elizabeth M.K. Divya G. Manoj Kumar M.S. Rajasree LBS Institute of Technology of Women Trivandrum Kerala India Computer Science & Engineering Government College of Engineering Trivandrum Kerala India

Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. This paper focuses on an efficient algorithm for recognizing the handwritten Malayalam characters. Malayalam OCR is a complex task owing to the various character scripts available and more importantly the difference in ways in which the characters are written. The dimensions are never the same and may be never mapped on to a square grid unlike English characters. Here we propose an algorithm which can accept the scanned image of handwritten characters as input and to produce the editable Malayalam characters in a predefined format as output without applying any resizing or skeletonization methods but still can produce much accurate results. Characters are grouped in to different classes based on their HLH intensity patterns. These patterns are separated from the image and fed for recognition. Algorithm is tested for 4 sets of samples ranging 661 letters in the noiseless environment and produces an accuracy of 88%.

关键词： Character recognition Optical character recognition software pattern recognition Handwriting recognition Feature extraction Artificial neural networks Shape Machine learning Isolation technology Image recognition

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An Electronic Nose System Based on an Array of Carbon Nanotubes Gas Sensors with pattern recognition Techniques

An Electronic Nose System Based on an Array of Carbon Nanotu...

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international conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Zikai Zhao Guohua Hui Coll. of Mech. & Electr. Eng. China Jiliang Univ. Hangzhou China Coll. of Food Sci. & Biotechnol. Zhejiang Gongshang Univ. Hangzhou China

Abstract-This paper presents design of an electronic nose based on an array of aligned multi-walled carbon nanotubes (MWNT) ionization gas sensors and pattern recognition techniques for gas detection. The raw data, including discharge voltages and currents, is acquired by measurement of sensor array response and transformed to the computer by peripheral circuit, and processed by Principal Components Analysis (PCA). Back-propagation neural networks (BPNN) are applied to determine gas varieties. Results demonstrate the developed electronic nose system is capable to identify target gases successfully and is promising for field applications.

关键词： Sensor arrays Electronic noses Carbon nanotubes Gas detectors pattern recognition Principal component analysis Ionization Voltage Current measurement Circuit analysis computing

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Photonic reservoir computing: A new approach to optical information processing

Photonic reservoir computing: A new approach to optical info...

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international conference on Transparent Optical Networks

作者： Kristof Vandoorne Martin Fiers David Verstraeten Benjamin Schrauwen Joni Dambre Peter Bienstman Photonics Research Group Department of Information Technology Ghent University IMEC Ghent Belgium PARIS Department of Electronics and Information Systems Ghent University Ghent Belgium

ISBN: (纸本)9781424477999;9781424477975

Despite ever increasing computational power, recognition and classification problems remain challenging to solve. Recently advances have been made by the introduction of the new concept of reservoir computing. This is a methodology coming from the field of machine learning and neural networks and has been successfully used in several pattern classification problems, like speech and image recognition. The implementations have so far been in software, limiting their speed and power efficiency. Photonics could be an excellent platform for a hardware implementation of this concept because of its inherent parallelism and unique nonlinear behaviour. We propose using a network of coupled Semiconductor Optical Amplifiers (SOA) and show in simulation that it could be used as a reservoir by comparing it on a benchmark speech recognition task to conventional software implementations. In spite of several differences, they perform as good as or better than conventional implementations. Moreover, a photonic implementation offers the promise of massively parallel information processing with low power and high speed. We will also address the role phase plays on the reservoir performance.

关键词： Reservoirs Optical computing Information processing Semiconductor optical amplifiers High speed optical techniques Nonlinear optics Machine learning Neural networks pattern classification Speech

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3rd conference on Smart Spaces, ruSMART 2010 and 10th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking, NEW2AN 2010

3rd Conference on Smart Spaces, ruSMART 2010 and 10th Intern...

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3rd conference on Smart Spaces, ruSMART 2010 and 10th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking, NEW2AN 2010

ISBN: (纸本)9783642148903

The proceedings contain 41 papers. The special focus in this conference is on Smart Spaces. The topics include: Physical Approach in Smart Homes: A Proposition and a Prototype;SMEO: A Platform for Smart Classrooms with Enhanced Information Access and Operations Automation;creative Approach to the Design and Prototyping of Experimental Smart Spaces, Case Studies from the Interactive Environments Minor;event recognition via Energy Efficient Voting for Wireless Sensor Networks;Evaluation of Multi-service CDMA Networks with soft Blocking;Design of MPLS over DWDM Architecture for Unicast and Anycast Flows;comparative Analysis of Sleep Mode Control Algorithms for Contemporary Metropolitan Area Wireless Networks;Determining Normalized Measure of Dispersion for Evaluating the Performance of IEEE 802.11;development of a System to Promote Eco-Driving and Safe-Driving;context-Awareness Enabling New Business Models in Smart Spaces;oligopoly Game Modeling for Cognitive Radio Environments;reducing the Number of States for Markovian Model of Optical Slotted Ring Network;performance Modelling of Automatic Identification System with Extended Field of View;performance Measures Computation for a Single Link Loss Network with Unicast and Multicast Traffics;realization of a Method of Matrix-Geometric Progression;mobility pattern Based Routing Algorithm for Delay/Disruption Tolerant Networks;heuristic Congestion Control for Message Deletion in Delay Tolerant Network;The FDPOO: A Flexible Delivering Platform with at-One-time and On-time Guarantees in Opportunistic Networks;A Distributed Telematics Peer-to-Peer (D-TP2P) Networking System for Service Discovery;Empirical Predictor of TCP Throughput on a Multihop Wireless Path;a Middleware Architecture for Safety Critical Ambient Intelligence Applications.

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A New Method of Data Reduction in Inconsistent Decision Tables

A New Method of Data Reduction in Inconsistent Decision Tabl...

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IEEE international conference on Granular computing (GRC)

作者： Shaobo Deng Min Li Sujie Guan Lian Chen Department of Computer Science & Technology Nanchang Institute of Technology Nanchang Jiangxi China Department of Computer Science and Application University of Nanchang Nanchang Jiangxi China

For inconsistent decision tables, this paper presents a new data reduction idea. Compared with the traditional data reduction method, the first step in this paper is attribute value reduction, then this paper simply deletes the inconsistent individuals sets. The last step is attribute reduction, which could avoid the negative factor of inconsistent individuals set.

关键词： Set theory Cognition Computers Computer science Complexity theory pattern recognition Partitioning algorithms

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EMD Strategy for activation detection in functional MRI of the human brain

EMD Strategy for activation detection in functional MRI of t...

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作者： Zheng, Tianxiang Yangt, Lihua Jiang, Tianzi Department of Tourism Management Shenzhen Tourism College Jinan University Shenzhen China Dept. of Sci. Computing and Computer Application School of Mathematics and Computational Science Sun Yat-sen University Guangzhou China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424472369

This article investigates how the Empirical Mode Decomposition (EMD) algorithm, a newly-developed and effective technique in the fields of signal processing and time-frequency analysis, is introduced and applied to activation detection in task-related functional Magnetic Resonance Imaging (fMRI) of the human brain. The method is illustrated using fMRI data simulated under one paradigm as well as one real dataset, and its performance is compared to those of a leading model based (General Linear Model - GLM) and a leading data-driven (Region Growing Method - RGM) approach. It is concluded that the proposed method achieves much better performance than the computationally inefficient RGM and is slightly more sensitive than GLM. Experimental results support its efficiency and sensitivity, which indicates that it is to become a viable alternative to the fMRI analysis. © 2010 IEEE.

关键词： Empirical mode decomposition

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Fast Marine Route Planning for UAV Using Improved Sparse A* Algorithm

Fast Marine Route Planning for UAV Using Improved Sparse A* ...

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international conference on Genetic and Evolutionary computing (ICGEC)

作者： Xin Yang Ming-yue Ding Cheng-ping Zhou Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China School of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Institute for Pattern Recognition and Artificial Intelligence (IPRAI) State Key Laboratory for Multispectral Information Processing Technologies Huazhong University of Science and Technology Wuhan Hubei China

This paper focuses on route planning, especially for unmanned aircrafts in marine environment. Firstly, new heuristic information is adopted such as threat-zone, turn maneuver and forbid-zone based on voyage heuristic information. Then, the cost function is normalized to obtain more flexible and reasonable routes. Finally, an improved sparse A* search algorithm is employed to enhance the planning efficiency and reduce the planning time. Experiment results showed that the improved algorithm for aircraft in maritime environment could find a combinational optimum route quickly, which detoured threat-zones, with fewer turn maneuver, totally avoiding forbid-zones, and shorter voyage.

关键词： Unmanned aerial vehicles Planning Synthetic aperture sonar Cost function Algorithm design and analysis Heuristic algorithms Leg

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Adaptive multi-cue fusion for visual target tracking based on uncertainly measure

Adaptive multi-cue fusion for visual target tracking based o...

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international conference on Image and Vision computing New Zealand, IVCNZ

作者： Xin Gu Haitao Wang Lingfeng Wang Chunhong Pan College of Automation Nanjing University of Aeronautics and Astronautics National Laboratory of Pattern Recognition (NLPR) Institute of Automation Chinese Academy of Sciences China National Laboratory of Pattern Recognition (NLPR) Chinese Academy of Sciences

ISBN: (纸本)9781424496297

This paper presents a novel adaptive tracking algorithm that fuses multiple cues based on feature uncertainty measurement in the particle filter framework. We first introduce a self-adaptive multi-cue fusion strategy, which overcomes the drawbacks of the traditional product fusion and sum fusion strategies. Furthermore, the proposed strategy effectively sharpens the distribution of the fused posterior as well as makes the tracking results less sensitive to the noise. Then, based on the fact that tracking failure often happens in the cases of low discriminative abilities of the observed features, we define a new feature uncertainty measurement. The proposed uncertainty measurement is thereafter used to adaptively adjust the relative contributions of different cues to tracking. An extensive number of comparative experiments show that the proposed tracking algorithm is more stable and robust than the single feature, product fusion, and sum fusion tracking algorithms.

关键词： Image edge detection Robustness

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Sample constraint clustering and it's applications in pattern recognition

Sample constraint clustering and it's applications in patter...

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international conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Shibin Xuan Yiguang Liu College of Computer Sichuan University Chengdu China College of Maths and Computer Science Guangxi University for Nationalities Nanning China

In the pattern recognition subspace method, the researcher has paid more attention to extract feature subspace, then expressed individual prototype with the training sample mean. Because the number of training sample is limited, there is certain difference between the sample mean and the individual prototype. In order to reduce this difference, a sample restraint clustering algorithm was proposed, which make up of it's clustering objective function with the Fisher criterion, and it's goal lies in minimizing within classes and maximizing between classes. The recurrence formula computing each cluster centroid is derived direct from the objective function. In the random produced sample space, the clustering experiment indicated the proposed method is able to reduce disparity between cluster centroid and the individual prototype. In the face recognition experiment, the positive recognition ratio of some algorithms may be improved when it's prototype is replaced with cluster centroid calculated by the proposed algorithm rather than the mean of training samples.

关键词： Clustering algorithms Prototypes Training Feature extraction Classification algorithms Face recognition

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An Efficient Braille Cells recognition

An Efficient Braille Cells Recognition

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international conference on Wireless Communications, Networking and Mobile computing (WiCom)

作者： AbdulMalik S. Al-Salman Ali El-Zaart Yousef Al-Suhaibani Khaled Al-Hokail AbdulAziz O. Al-Qabbany Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

This paper presents a new algorithm for Braille cells recognition using image processing technique. Scanned Braille document is composed from three classes of gray-level: (i) background, (ii) recto dots, and (iii) verso dots. We segment the Braille image using a stability thresholding method with a mixture of Beta distributions. To ensure correct detection and extraction of dots composing Braille cells, a grid is formed to contain the Braille dots. We identified a recto dot by a light region that exists above a dark region using the segmented image. In the same way, we identify a verso dot in double sided document by a light region that exists below a dark region. After having recto and verso dots, Braille cells are then recognized based on the standard regrouping of dots. Experimentation showed that Braille cells composing are automatically identified from those grids with excellent accuracy.

关键词： Image segmentation Image recognition pattern recognition Optical imaging Optical sensors Power system stability software

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