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Detection and classification of diseases of Grape plant using opposite colour Local Binary pattern feature and machine learning for automated Decision Support System

Detection and classification of diseases of Grape plant usin...

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international conference on Signal Processing and Integrated Networks (SPIN)

作者： Harshal Waghmare Radha Kokare Yogesh Dandawate Dept. of Electronics and Telecommunication Engineering Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9781467391986

Plant diseases cause major economic and production losses as well as curtailment in both quantity and quality of agricultural production. Now a day's, for supervising large field of crops there is been increased demand for plant leaf disease detection system. The critical issue here is to monitor the health of the plants and detection of the respective diseases. Studies show that most of the plant disease can be diagnosed from the properties of the leaf. Thus leaf based disease analysis for plants is an exciting new domain. The technique proposed for identification of plant disease through the leaf texture analysis and pattern recognition. In this work we focus on Grapes plant leaf disease detection system. The system takes a single leaf of a plant as an input and segmentation is performed after background removal. The segmented leaf image is then analyzed through high pass filter to detect the diseased part of the leaf. The segmented leaf texture is retrieved using unique fractal based texture feature. Fractal based features are locally invariant in nature and therefore provides a good texture model. The texture of every independent disease will be different. The extracted texture pattern is then classified using multiclass SVM. The work classifies focus on major diseases commonly observed in Grapes plant which are downy mildew & black rot. The proposed approach avails advice of agricultural experts easily to farmers with the accuracy of 96.6%.

关键词： Diseases Feature extraction Support vector machines Image color analysis Agriculture Pipelines Decision support systems

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Identification of Tigers (Panthera Tigris) through their pugmark using pattern recognition using Android phone application

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

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international conference on Computing for Sustainable Global Development (INDIACom)

作者： Rushikesh Dhande Vijay Gulhane Information Technology Department Sant Gadge Baba Amravati University Amravati INDIA

ISBN: (纸本)9781467394178

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： Smart phones Cameras Servers Databases Algorithm design and analysis Wildlife Image processing

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3rd international Workshop on Similarity-Based pattern recognition, SIMBAD 2015

作者： Feragen, Aasa Pelillo, Marcello Loog, Marco University of Copenhagen Copenhagen Denmark DAIS Università Ca' Foscari Venezia Venezia Mestre Italy Delft University of Technology Delft Zuid-Holland Netherlands

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Electronic Nose as an NDT Tool for Aerospace Industry 3

Electronic Nose as an NDT Tool for Aerospace Industry

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3rd international conference Frontiers in Diagnostic Technologies

作者： De Vito, Saverio Massera, Ettore Miglietta, Mara Fattoruso, Grazia Di Francia, Girolamo ENEA CR Portici Ple E Fermi 1 I-80055 Portici NA Italy

Artificial olfaction is an emerging technology aiming to develop tools for easy, rapid and mobile gas mixture analysis. So far, its application to several application fields is under investigation with some commercial solution already deployed. In this work we present the results of the development process for an electronic nose devised for NDT in aerospace industry focusing on its pattern recognition stage. (C) 2014 The Authors. Published by Elsevier B.V.

关键词： Electronic Nose pattern recognition Non Desctructive Tests Aerospace Industry

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3rd international conference on pattern recognition Applications and Methods, ICPRAM 2014

3rd International Conference on Pattern Recognition Applicat...

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3rd international conference on pattern recognition Applications and Methods, ICPRAM 2014

ISBN: (纸本)9783319255293

The proceedings contain 18 papers. The special focus in this conference is on pattern recognition Applications and Methods. The topics include: Aggregation of biclustering solutions for ensemble approach;fuzzy c-means stereo segmentation;intra-class variance among multiple samples of the same person’s fingerprint in a cooperative user scenario;kernel matrix completion for learning nearly consensus support vector machines;an empirical comparison of support vector machines versus nearest neighbour methods for machine learning applications;improving the detection of relations between objects in an image using textual semantics;a TOF-aided approach to 3d mesh-based reconstruction of isometric surfaces;segmentation of tomatoes in open field images with shape and temporal constraints;fast and accurate pedestrian detection in a truck’s blind spot camera;comparing different labeling strategies in anomalous power consumptions detection;an efficient shape feature extraction, description and matching method using GPU;utilization of multiple sequence analyzers for bibliographic information extraction;statistically representative cloud of particles for crowd flow tracking;preserving maximum color contrast in generation of gray images and real-time facial analysis in still images and videos for gender and age estimation.

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Tuning the parameters of an integrate and fire neuron via a genetic algorithm for solving pattern recognition problems

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NEUROCOMPUTING 2015年 148卷 187-197页

作者： Cachou, Aleister Vazquez, Roberto A. La Salle Univ Intelligent Syst Grp Col Hipodromo Condesa 06140 DF Mexico

Recently, it has been proven that spiking neurons can be used for some pattern recognition problems. Nonetheless, the spiking neurons models have many parameters that have to be manually adjusted in order to achieve the desired behavior. This paper has the purpose of showing an optimization method for one such model, the Integrate & Fire spiking model (I&F). A genetic algorithm (GA) is proposed to automatically adjust the parameters, removing the need of manual tuning and increasing efficiency. Initial experimentation is done by tuning the I&F model parameters by hand, to confirm the importance and relevance of determining the best parameter values. The GA is then used to automatically tune different parameter combinations of the pattern recognition model, which uses the I&F neuron as core, to determine which parameters are worth including in the GA. The proposed method was tested with five different datasets, where no change was required to apply the model to each. Very good results were achieved in all test cases, but experiments where parameters of the neuron model were included converged faster. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Spiking neuron Genetic algorithm pattern recognition Integrate and fire

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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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3rd international Workshop on Similarity-Based pattern recognition, SIMBAD 2015

3rd International Workshop on Similarity-Based Pattern Recog...

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3rd international Workshop on Similarity-Based pattern recognition, SIMBAD 2015

ISBN: (纸本)9783319242606

The proceedings contain 16 papers. The special focus in this conference is on Similarity-Based pattern recognition. The topics include: A novel data representation based on dissimilarity increments;characterizing multiple instance datasets;supervised learning of diffusion distance to improve histogram matching;similarity analysis from limiting quantum walks;introducing negative evidence in ensemble clustering application in automatic ECG analysis;dissimilarity representations for low-resolution face recognition;deep metric learning using triplet network;cluster merging based on dominant sets;an adaptive radial basis function kernel for support vector data description;robust initialization for learning latent dirichlet allocation;unsupervised motion segmentation using metric embedding of features;transitive assignment kernels for structural classification;large scale indefinite kernel fisher discriminant;similarity-based user identification across social networks;dominant-set clustering using multiple affinity matrices;discovery of salient low-dimensional dynamical structure in neuronal population activity using hopfield networks;distance-based network recovery under feature correlation;a matrix factorization approach to graph compression;can the optimum similarity matrix be selected before clustering for graph-based approaches? and approximate spectral clustering with utilized similarity information using geodesic based hybrid distance measures.

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3rd international conference on Human-Agent Interaction, HAI 2015

作者： Choi, Hyunsoek Park, Hyeyoung School of Electrical Engineering and Computer Science Kyungpook National University 80 Daehakro Bukgu Daegu Korea Republic of

ISBN: (纸本)9781450335270

In order to make machines able to recognize various patterns, it is important to define an appropriate function for measuring similarities between different objects. Conventional similarity measures are devised mainly for 1D vector data, which may lead to loss of information of 2D matrix data. We cast the calculation of similarity between two matrices as a neural network problem, and design the architecture for learning a similarity measure. We provide experiments on real 2D matrix data in the face recognition and gesture recognition, where we show that the learning of a similarity measure leads to improvements in the performance of the recognition problem. Also we compare the performance of the proposed measure with conventional distance measures for 2D matrix data. © 2015 ACM.

关键词： Matrix algebra

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Divide-and-Conquer Computational Approach to Principal Component Analysis 3

Divide-and-Conquer Computational Approach to Principal Compo...

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3rd international conference on Frontiers in Intelligent Computing - Theory and Applications (FICTA)

作者： Kadappa, Vijayakumar Negi, Atul BMS Coll Engn Dept Comp Applicat Bangalore Karnataka India Univ Hyderabad Sch CIS Hyderabad Andhra Pradesh India

ISBN: (纸本)9783319119328

Divide-and-Conquer (DC) paradigm is one of the classical approaches for designing algorithms. Principal Component Analysis (PCA) is a widely used technique for dimensionality reduction. The existing block based PCA methods do not fully comply with a formal DC approach because (i) they may discard some of the features, due to partitioning, which may affect recognition;(ii) they do not use recursive algorithm, which is used by DC methods in general to provide natural and elegant solutions. In this paper, we apply DC approach to design a novel algorithm that computes principal components more efficiently and with dimensionality reduction competitive to PCA. Our empirical results on palmprint and face datasets demonstrate the superiority of the proposed approach in terms of recognition and computational complexity as compared to classical PCA and block-based SubXPCA methods. We also demonstrate the improved gross performance of the proposed approach over the block-based SubPCA in terms of dimensionality reduction, computational time, and recognition.

关键词： pattern recognition Dimensionality Reduction Principal Component Analysis Block based PCA Divide-and-Conquer approach

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