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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

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State recognition of Egg Embryo in Vaccines Production Based on SVM 5

State Recognition of Egg Embryo in Vaccines Production Based...

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5th international conference on Mechanical, Automotive and Materials Engineering (CMAME)

作者： Xu, Yanwei Chen, Menghui Xie, Tancheng Henan Univ Sci & Technol Sch Mechatron Engn Luoyang 471023 Peoples R China

ISBN: (纸本)9781538604328

the method for state recognition of egg embryo in biological vaccines production based on computer image processing and support vector machine was researched. Firstly, the median filtering method was applied to eliminate noises in the images of egg embryo that were classified by the requirements of practical production, then the threshold segmentation method was used to segment the images, then the blood vessels and black blocks in the egg embryo images were selected as major characteristics to extract. the decision tree classification model with structure of binary tree was built on support vector machine, and the model was trained with the toolkit LIBSVM, the penalty factor C = 2, RBF kernel parameter gamma=3.0512e-05 and the precision of cross validation accuracy is 98.913% Finally, 100 egg embryos were randomly selected as the test samples to do pattern recognition, and compared with manual test result. the comparison result showed that the discriminant accuracy of SVM classifier on weak embryo, polluted embryo or dead embryo was 100%, and it of SVM classifier on live embryo was 94.62%.

关键词： egg embryo pattern recognition support vector machine computer image processing

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Text localization in historical document images with local binary patterns and variance models

Text localization in historical document images with local b...

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Bhowmik, Tapan Kumar Kar, Manika LITIS EA-4108 Université de Rouen France Departamento de Engenharia Informática Universidade do Porto Portugal

ISBN: (纸本)9783642450617

In this paper, we explore the utility of Local Binary pattern (LBP) descriptors and variance measure towards the development of efficient techniques in order to segment a large collection of historical machine printed document pages. the result of segmentation will help us to organize the document pages in a structural format, which is useful in many applications like historical document access. In our experiments, three basic reference models namely background, text and image models are used to segment various non-text information together with the text. the method is tested on an archive of Portuguese historical documents and shows promising results. © Springer-Verlag 2013.

关键词： Local binary pattern

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pattern recognition - 5th Mexican conference, MCPR 2013, Proceedings

Pattern Recognition - 5th Mexican Conference, MCPR 2013, Pro...

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5th Mexican conference on pattern recognition, MCPR 2013

ISBN: (纸本)9783642389887

the proceedings contain 38 papers. the topics discussed include: a fuzzy scheme for gait cycle phase detection oriented to medical diagnosis;virtual target formulation for singularity-free visual control using the trifocal tensor;assessing the quality level of corn tortillas with inductive characterization and digital image analysis;3D representation for object detection and verification;3D tracking and control of UAV using planar faces and monocular camera;third-eye stereo analysis evaluation enhanced by data measures;counting pedestrians in bidirectional scenarios using zenithal depth images;tracklet reidentification in crowded scenes using bag of spatio-temporal histograms of oriented gradients;LIDAR and panoramic camera extrinsic calibration approach using a pattern plane;video images fusion to improve iris recognition accuracy in unconstrained environments;and perception aptitude improvement of an odor sensor: model for a biologically inspired nose.

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Entropy Analysis of Two Phase Flow pattern Identification in Vertical Tube 5

Entropy Analysis of Two Phase Flow Pattern Identification in...

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5th international conference on Advances in Energy Resources and Environment Engineering (ICAESEE)

作者： Lu, Kun Ma, Longxin Li, Gen Shang, Wei Feng, Yixuan China Huadian Elect Power Res Inst Co Ltd Hangzhou 310030 Zhejiang Peoples R China

this paper aims to analyze the time domain marginal spectral entropy of differential pressure signals collected from the gas-liquid two-phase flow pattern vertical tube bundle channel on the experimental platform. By comparing the visualized and measured differential pressure signals, four flow patterns were found, namely, bubble flow, bubble-mixed flow, agitated flow, and annular flow. the marginal spectral entropy values of the four flow patterns are calculated, and it is found that the spectral entropy distribution regions of the different flow patterns are different. Putting the aforementioned four flow patterns that is regarded as the feature quantity into artificial neural network support vector machine for flow pattern recognition. the experimental results show that the marginal spectral entropy can better reflect the flow difference between different flow patterns. the support vector machine has the advantages of fast calculation speed and high recognition rate. the overall recognition rate of the four flow patterns (the transition flow is included) is as high as 95.31% by combing the marginal spectral entropy with the support vector machine, which is suitable for online identification of flow patterns.

关键词： Flow patterns

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Convolutional Neural Network Training with Artificial pattern for Bangla Handwritten Numeral recognition 5

Convolutional Neural Network Training with Artificial Patter...

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5th international conference on Informatics, Electronics and Vision (ICIEV)

作者： Akhand, M. A. H. Ahmed, Mahtab Rahman, M. M. Hafizur Khulna Univ Engn & Technol Dept Comp Sci & Engn Khulna Bangladesh Int Islamic Univ Malaysia KICT Dept Comp Sci Selangor Malaysia

ISBN: (纸本)9781509012695

recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. the progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high-dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, a CNN based method has been investigated for Bangla handwritten numeral recognition. A moderated pre-processing has been adopted to produce patterns from handwritten scan images. On the other hand, CNN has been trained with the patterns plus a number of artificial patterns. A simple rotation based approach is employed to generate artificial patterns. the proposed CNN with artificial pattern is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset.

关键词： Bangla Numeral Convolutional Neural Network pattern Generation Handwritten Numeral recognition

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Persian Handwritten Digits recognition by Using Zoning and Histogram Projection

Persian Handwritten Digits Recognition by Using Zoning and H...

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3rd Joint conference of AI and Robotics / 5th RoboCup Iran Open international Symposium

作者： Nooraliei, Amir Islamic Azad Univ Qazvin Branch Dept Elect Comp & IT Engn Qazvin Iran

ISBN: (纸本)9781467363150

In this paper, Persian handwritten digits reorganization by using zoning features and projection histogram for extracting feature vectors with 69-dimensions is presented. In classification stage, support vector machines (SVM) with three linear kernels, polynomial kernel and Gaussian kernel have been used as classifier. We tested our algorithm on the dataset that contained 8600 samples of Persian handwritten digits for performance analysis. Using 8000 samples in learning stage and another 600 samples in testing stage. the results got with use of every three kernels of support vector machine and achieved maximum accuracy by using Gaussian kernel with gamma equal to 0.16. In pre-processing stage only image binarization is used and all the images of this dataset had been normalized at center with size 40x40. the recognition rate of this method, on the test dataset 97.83% and on all samples of dataset 100% was earned.

关键词： pattern recognition Optical character recognition Support vector machine Persian handwritten digits

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Random weighting through linear programming into intracellular transporters of rice metabolic network

Random weighting through linear programming into intracellul...

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5th international conference on pattern recognition and Machine Intelligence, PReMI 2013

作者： Shaw, Rahul Kundu, Sudip Department of Biophysics Molecular Biology and Bioinformatics University of Calcutta Kolkata 700 009 India

ISBN: (纸本)9783642450617

An eukaryotic cell has different compartments which are specific to different biological activities. the total cellular metabolism is also compartmentalized. the intracellular transporters within a cell are responsible to transport some of the metabolites of one compartment to other. We formulate a model to understand the utility of different transporters. Here, we have taken a partially compartmentalized genome scale metabolic model of rice (Oryza sativa). Depending on the gene-expression, the transporters available to transport the metabolites from one compartment to other would change. We study the effect of transporter's capacity on the overall metabolism. We find that depending on the effectiveness of transporters, the photon demand for a rice leaf's biochemical machinery to synthesize the necessary biomass from inorganic nutrients, changes upto three fold. We also observe, interactions of mitochondrial and chloroplastid reactions are associated with this change. © Springer-Verlag 2013.

关键词： Linear programming

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Image and Signal Processing - 5th international conference, ICISP 2012, Proceedings

Image and Signal Processing - 5th International Conference, ...

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5th international conference on Image and Signal Processing, ICISP 2012

ISBN: (纸本)9783642312533

the proceedings contain 67 papers. the topics discussed include: Bayesian image matting using infrared and color cues;salient pixels and dimensionality reduction for display of multi/hyperspectral images;SVM and haralick features for classification of high resolution satellite images from urban areas;multi-model approach for multicomponent texture classification;simultaneous multispectral imaging and illuminant estimation using a stereo camera;kernel-based Laplacian smoothing method for 3D mesh denoising;embedded real-time video processing system on FPGA;edge preserving image fusion based on contourlet transform;selecting vision operators and fixing their optimal parameters values using reinforcement learning;a phase congruency based document binarization;methodology for acoustic characterization of a labial constraint in speech production;and nonlinear blind source separation applied to a simple bijective model.

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A comparative analysis on the performance of different handcrafted descriptors over thermal and low resolution visible image dataset 5

A comparative analysis on the performance of different handc...

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5th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and Computer Engineering (UPCON)

作者： Kumar, Sumit Singh, Satish Kumar IIIT Allahabad Allahabad Uttar Pradesh India

ISBN: (纸本)9781538650028

In the past visible light face recognition has been considered as an authentic biometric trait and a lot of research has been done for performance enhancement of the same. But the impact of illumination variation over the recognition performance has been a challenging task to overcome when we take outdoor conditions into consideration whereas thermal infrared features are robust to the illumination variations as it focus on changes of temperature distribution on facial muscles and blood vessels. these temperature variations in itself creates a texture. the other major reason for the need of thermal trait is the night time surveillance when there is low or minimal amount of light thus is unable to illuminate the face. thermal facial images is majorly used in several military operations as covert data acquisition carry challenges in its own ways and the visible light images sometimes fail miserably to fulfil the desired outcome due to its dependence on lighting and illumination variations. In this work we have done a comparative study on the performance of different handcrafted descriptors over thermal and visible images using different distance measures. the paper divides the proposed descriptors in 2 different sets i.e. lower order derivative based and higher order derivative based descriptors. We have compared the performance of different lower order derivative based descriptors over the higher order derivative based on different distance measures and tried to analyze the limitations and delimitations of handcrafted descriptors over multispectral range of images.

关键词： Local Binary pattern (LBP) local derivative pattern (LDP) local vector pattern (LVP) local gradient hexa-pattern (LGHP) Generalized distance local binary pattern (GDLBP) Average retrieval rate (ARR) Average precision of retrieval (APR) Sample Size (SS) Mid wave infrared (MWIR) Long wave infrared (LWIR) Near Infrared (NIR)

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the Feature Extraction and pattern recognition of Partial Discharge Type Using Fnergy Percentage of Wavelet Packet Coefficients and Support Vector Machines 5

The Feature Extraction and Pattern Recognition of Partial Di...

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5th international conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Xu, Jia Niu, Haiqing Hu, Riliang South China Univ Technol Sch Elect Power Guangzhou 510640 Guangdong Peoples R China Southern Power Grid Dongguan Power Supply Bur Dongguan 523129 Peoples R China

ISBN: (纸本)9781467371063

Partial discharge is an important cause of the deterioration of the cable insulation condition, and also an important manifestation of the deteriorated insulation condition. Partial discharge detection for cable insulation is an important means to find the cable insulation defects and assess state of the cable insulation. Partial discharge signals from different sources have great harm to the power equipment, so pattern identification is an important purpose in this research. First, the four kinds of discharge waveforms are processed by dc-noising preprocessing, then discharge waveforms are decomposed by wavelet packet, and finally the energy percentage in different frequency bands can he obtained. Studies show that when the type of discharge signal is different, the wavelet packet coefficients in the distribution of each band is also different. So energy percentage of the wavelet packet coefficients can be used for discharge signal feature recognition. In this paper, SVM binary classification is first extended to multi-classification by M-ary algorithm, then the feature vectors composed by energy percentage of the wavelet packet coefficients arc inputted into SVM for recognition. the recognition results of test samples show that feature vectors composed by the percentage of energy of wavelet packet coefficients can well reflect the characteristics of the original signal, and the method based on SVM has better recognition performance.

关键词： partial discharge electric cable wavelet packet decomposition percentage of energy feature extraction support vector machine pattern recognition

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