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Offline Malayalam Character recognition: A Comparative Study Using Multiple Classifier Combination Techniques 1

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3rd international conference on Information System Design and Intelligent Applications (INDIA)

作者： Chacko, Anitha Mary M. O. Kumar, K. S. Anil Sree Ayyappa Coll Dept Comp Sci Chengannur 689109 Kerala India

ISBN: (数字)9788132227571

ISBN: (纸本)9788132227571;9788132227564

Malayalam character recognition has gained immense popularity in the past few years. The intrinsic challenges present in this domain along with the large character set of Malayalam further complicate the recognition process. Here we present a comparative evaluation of different multiple classifier combination techniques for the offline recognition of Malayalam characters. We have extracted three different features from the preprocessed character images-Density features, Run-length count and Projection profiles. These features are fed as input to three different neural networks and finally the results of these three networks were combined and evaluated using six different classifier combination methods: Max Rule, Sum Rule, Product Rule, Borda Count Rule, Majority Voting and Weighted Majority voting schemes. The best recognition accuracy of 97.67 % was attained using the Weighted Majority scheme considering top 3 results.

关键词： pattern recognition Multiple classifier system Neural networks Character recognition Classifier combination

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Accelerated Variational Inference for Beta-Liouville Mixture Learning with Application to 3D shapes recognition 3

Accelerated Variational Inference for Beta-Liouville Mixture...

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3rd international conference on Control, Decision and Information Technologies (CoDIT)

作者： Fan, Wentao Al-Osaimi, Faisal R. Bouguila, Nizar Du, Ji-Xiang Huaqiao Univ Dept Comp Sci & Technol Xiamen Peoples R China Umm Al Qura Univ Dept Comp Engn Coll Comp Syst Mecca Saudi Arabia Concordia Univ CIISE Montreal PQ Canada

ISBN: (纸本)9781509021888

Beta-Liouville mixture models have achieved measurable success in many computer vision and pattern recognition applications. In this paper, we develop a novel algorithm to learn this particular kind of models that have been shown to be very efficient for the clustering of proportional data. Our algorithm is based on an accelerated version of the variational Bayes approach. Experiments show that the developed algorithm work very well for the categorization of 3D shapes.

关键词： Infinite mixture variational Bayes Beta-Liouville 3D shapes

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Proceedings - 2016 3rd international conference on Advances in Computing, Communication and Engineering, ICACCE 2016

Proceedings - 2016 3rd International Conference on Advances ...

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3rd international conference on Advances in Computing, Communication and Engineering, ICACCE 2016

ISBN: (纸本)9781509025763

The proceedings contain 79 papers. The topics discussed include: aircycle proof-of-concept: work towards using gamification and IoT to fight the global obesity crisis;exploring RSSI dependency on height in uhf for throughput optimization;analysis of Bluetooth and Wi-Fi interference in smart home networks;location based analysis of AODV performance in the presence of black hole nodes;semi-autonomous vehicles: towards a conceptual model of compliance with owner manual standards;implementing a compact data format for Bluetooth and 3G communication to monitor remote pipelines;a user scheduling scheme in LTE/LTE-a networks for a mixed traffic environment;design considerations of a topology control prototype for wireless mesh networks;optimized survivability scheme to safeguard end to end QoS in the next generation optical networks;the feasibility of a WLAN based power subsation monitoring platform;pattern recognition technique to eliminate multipath and radio-frequency interference in an automated antenna measurement system;optimal power control strategy of a distributed energy system incorporating demand response;variation of altitude on the variance of angle of arrival fluctuations for optical beam propagation in free space optical communications;an empirical analysis of semantic web mechanisms for storage and query of ontologies in relational databases;the influence of external actors in the formulation of national information and communications technology policies in developing countries: case of Swaziland;and capacity improvement for VOiP based two-tier CRN using space-time spectrum sensing.

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The Challenge of Brain Complexity A Brief Discussion about a Fractal Intermittency-based Approach 3

The Challenge of Brain Complexity <i>A Brief Discussion abou...

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3rd international conference on Physiological Computing Systems (PhyCS)

作者： Paradisi, Paolo Righi, Marco Barcaro, Umberto ISTI CNR Ist Sci & Tecnol Informaz A Faedo Via G Moruzzi 1 I-56124 Pisa Italy BCAM Alameda Mazarredo 14 Bilbao 48009 Bizkaia Spain Univ Pisa Dipartimento Informat Largo B Pontecorvo 3 I-56127 Pisa Italy

ISBN: (纸本)9789897581977

In the last years, the complexity paradigm is gaining momentum in many research fields where large multidimensional datasets are made available by the advancements in instrumental technology. A complex system is a multi-component system with a large number of units characterized by cooperative behavior and, consequently, emergence of well-defined self-organized structures, such as communities in a complex network. The self-organizing behavior of the brain neural network is probably the most important prototype of complexity and is studied by means of physiological signals such as the ElectroEncephaloGram (EEG). Physiological signals are typically intermittent, i.e., display non-smooth rapid variations or crucial events (e.g., cusps or abrupt jumps) that occur randomly in time, or whose frequency changes randomly. In this work, we introduce a complexity-based approach to the analysis and modeling of physiological data that is focused on the characterization of intermittent events. Recent findings about self-similar or fractal intermittency in human EEG are reviewed. The definition of brain event is a crucial aspect of this approach that is discussed in the last part of the paper, where we also propose and discuss a first version of a general-purpose event detection algorithm for EEG signals.

关键词： Biomedical Signal Processing Electroencephalogram Brain Events Fractal Intermittency Threshold Analysis pattern recognition Complex Systems

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Maritime pattern Extraction from AIS data using a Genetic Algorithm 3

Maritime Pattern Extraction from AIS data using a Genetic Al...

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3rd IEEE/ACM international conference on Data Science and Advanced Analytics (DSAA)

作者： Dobrkovic, Andrej Iacob, Maria-Eugenia van Hillegersberg, Jos Univ Twente Ind Engn & Business Informat Syst POB 217 NL-7500 AE Enschede Netherlands

ISBN: (纸本)9781509052066

The long term prediction of maritime vessels' destinations and arrival times is essential for making an effective logistics planning. As ships are influenced by various factors over a long period of time, the solution cannot be achieved by analyzing sailing patterns of each entity separately. Instead, an approach is required, that can extract maritime patterns for the area in question and represent it in a form suitable for querying all possible routes any vessel in that region can take. To tackle this problem we use a genetic algorithm (GA) to cluster vessel position data obtained from the publicly available Automatic Identification System (AIS). The resulting clusters are treated as route waypoints (WP), and by connecting them we get nodes and edges of a directed graph depicting maritime patterns. Since standard clustering algorithms have difficulties in handling data with varying density, and genetic algorithms are slow when handling large data volumes, in this paper we investigate how to enhance the genetic algorithm to allow fast and accurate waypoint identification. We also include a quad tree structure to preprocess data and reduce the input for the GA. When the route graph is created, we add post processing to remove inconsistencies caused by noise in the AIS data. Finally, we validate the results produced by the GA by comparing resulting patterns with known inland water routes for two Dutch provinces.

关键词： Genetic Algorithms pattern recognition Data Mining Automatic Identification System Synchromodal Logistics

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Identification of Tigers (Panthera Tigris) through their Pugmark using pattern recognition using Android Phone Application 3

Identification of Tigers (Panthera Tigris) through their Pug...

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3rd international conference on Computing for Sustainable Global Development (INDIACom)

作者： Dhande, Rushikesh Gulhane, Vijay St Gadge Baba Amravati Univ Dept Informat Technol Amravati India

ISBN: (纸本)9789380544199

The tiger is bearing as the Power of the Gain and displays India's wildlife wealth. The Bengal Tiger was declared as the enclosing-embracing zoological of India in April 1973, adjacent to the beginning of Movement Tiger, to defend the tigers in India. The protection of wildlife and forests is a major responsibility of human being. The guidance of wildlife and forests is a prime culpability of sensual being. Material's power narrative to leave alone run after of all about movements by each tiger. They used radio collars on tiger shoulder and micro chips which is in tiger body to trace the tiger. These both are quite tough jobs. Another method is to track tiger is through their pugmarks. Additional approximate is to run after tiger is look over their pugmarks. Consent to Forest next of kin underpinning stamp the tiger by identifies their pugmarks. But all this distinction is culminate manually which is war cry nearly to that level of correctness. This paper is presenting method for identifying tiger through their pugmarks using image processing techniques. The pugmarks for many different tigers will be collected from the forest. The identification is based on matching of parameters stored in database.

关键词： Android phone camera individual identification internet connection Tiger pugmark (footprints)

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Fast Autonomous Crater Detection by Image Analysis-For Unmanned Landing on Unknown Terrain 7th

Fast Autonomous Crater Detection by Image Analysis-For Unman...

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7th international conference on Image and Signal Processing (ICISP)

作者： Sadhukhan, Payel Palit, Sarbani Indian Stat Inst 203BT Rd Kolkata 700108 India

ISBN: (纸本)9783319336183;9783319336176

Unmanned landing on unknown terrain such as planetary surfaces requires the in-situ estimation of surface irregularities like craters, ridges and other deformities. Moreover, to facilitate safe landing, the surface estimation has to be done in as little time as possible. In this paper, we present an algorithm to address the above two issues in the context of crater presence on the terrain. Detection of craters is done on images of the probable landing surfaces and the computation time required for the detection is subsequently reduced in the proposed method using image analysis approaches like standard deviation filtering, morphological operations and validation of crater presence by texture extraction. We have achieved a 85-89% true positive (TP) rate on large craters and 79-82% TP rate on small craters. We have conducted our experiments on real images of Mars and the Moon, collected by space-crafts named 2001 Mars Odyssey and the Lunar Reconnaissance Orbiter, respectively. Empirical evidences indicate that the proposed method achieves a commendable TP rate and a subsequent improvement in the time required for detection as compared to existing methodologies.

关键词： Crater detection Mathematical morphology Contrast change Texture analysis Image analysis

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Proceedings of 2016 international conference on Data and Software Engineering, ICoDSE 2016

Proceedings of 2016 International Conference on Data and Sof...

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3rd international conference on Data and Software Engineering, ICoDSE 2016

ISBN: (纸本)9781509056712

The proceedings contain 64 papers. The topics discussed include: automatic rhetorical sentence categorization on Indonesian meeting minutes;Chinese chess character recognition using direction feature extraction and backpropagation;classification based on constrained progressive sequential pattern mining: a proposed model;classification of Indonesian news articles based on latent dirichlet allocation;clustering technique for information requirement prioritization in specific CMSs;deep learning and distributional semantic model for Indonesian tweet categorization;fisheye zoom and semantic zoom on citation network visualization;focused crawler for the acquisition of health articles;and fraud detection based-on data mining on Indonesian e-procurement system (SPSE).

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Emotion recognition: A Step Ahead of Traditional Approaches 3rd

Emotion Recognition: A Step Ahead of Traditional Approaches

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3rd international conference on Information System Design and Intelligent Applications (INDIA)

作者： Agarwal, Surbhi Madhurima, Madhulika Azamgarh India

ISBN: (纸本)9788132227526;9788132227502

Emotion recognition is an intriguing issue these days. It affects essential applications in numerous regions for example surveillance, defense, financial services etc. Determining a particular expression from face images effectively is a crucial venture. In this paper, we have demonstrated a novel approach to recognize emotions displayed in video sequences. The authors have considered seven basic emotions measuring factors: anger, fear, disgust, happiness, sadness, surprise and neutral. These factors are constantly encountered in our day to day life. The focus of this paper is towards contemplates a combination of extended biogeography based optimization algorithm, support vector machines and local binary patterns to obtain the best possible results.

关键词： Support vector machine Biometrics Feature extraction Viola jones Linear binary pattern Extended

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3rd international conference on Innovations in Computer Science and Engineering, ICICSE 2015

3rd International Conference on Innovations in Computer Scie...

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3rd international conference on Innovations in Computer Science and Engineering, ICICSE 2015

ISBN: (纸本)9789811004179

The proceedings contain 36 papers. The special focus in this conference is on Innovations in Computer Science and Engineering. The topics include: Secure ATM door locking system using RFID;analysis of various parameters for link adaptation in wireless transmission;n-gram classifier system to filter spam messages from OSN user wall;a recent study of emerging tools and technologies boosting big data analytics;registration plate recognition using dynamic image processing and genetic algorithm;comparing the capacity, NCC, and fidelity of various quantization intervals on DWT;enhancing cloud computing server to use cloud safely and to produce infrastructure of high performance computing;3-D array pattern distortion analysis;high-security pipelined elastic substitution box with embedded permutation facility;an integrated approach to high-dimensional data clustering;performance analysis of network virtualization in cloud computing infrastructures on openstack;a shoulder-surfing resistant graphical password authentication scheme;a proposal for searching desktop data;low-power analog bus for system-on-chip communication;text clustering and text summarization on the use of side information;assessment of reusability levels on domain-specific components using heuristic function;reliable propagation of real-time traffic conditions in VANETS to evade broadcast storm;hybrid multi-objective optimization approach for neural network classification using local search;effectiveness of email address obfuscation on internet;how massive online data breaches impacts personal data in web;a survey on challenges in software development during the adoption of agile environment and data fusion approach for enhanced anomaly detection.

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