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Foliar fungal disease classification in banana plants using elliptical local binary pattern on multiresolution dual tree complex wavelet transform domain

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Information Processing in Agriculture 2021年第4期8卷 581-592页

作者： deepthy mathew C.Sathish Kumar KAnita Cherian Department of Electronics and Communication Engineering Rajiv Gandhi Institute of TechnologyAPJ Abdul Kalam Technological UniversityKottayam 686501India Department of Electronics and Communication Engineering Government Engineering CollegeIdukki 685603India Department of Plant Pathology College of HorticultureKerala Agricultural UniversityThrissur 680656India

The fungal diseases in banana cause major yield losses for millions of farmers around the *** detection of these diseases helps the farmers to devise successful management *** characteristic leaf blade discoloration pattern at the earlier stages of infection could be used to understand the onset of each *** paper demonstrates a methodology for classification of three important foliar diseases in banana,using local texture *** disease affected regions are identified using image enhancement and color *** images are converted to transform domain using three image transforms(DWT,DTCWT and Ranklet transform).Feature vector is extracted from transform domain images using LBP and its variants(ELBP,MeanELBP and MedianELBP).These texture based features are applied to five popular image classifiers and comparative performance analysis is done using ten-fold cross validation *** results showed best classification performance for ELBP features extracted from DTCWT domain(accuracy 95.4%,precision 93.2%,sensitivity 93.0%,Fscore 93.0%and specificity 96.4%).Compared with traditional methods of feature extraction,this novel method of fusing DTCWT with ELBP features has attained high degree of accuracy in precisely detecting and classifying fungal diseases in banana at an early stage.

关键词： Musa Plant disease classification Texture features Local binary pattern DWT Image classifiers

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Applications of Burr Ⅲ-Weibull quantile function in reliability analysis

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Statistical Theory and Related Fields 2023年第4期7卷 296-308页

作者： G.S.deepthy Nicy Sebastian N.Chandra Department of Statistics St.Thomas College(Autonomous)Thrissur affiliated to University of CalicutKeralaIndia Department of Statistics Ramanujan School of Mathematical SciencesPondicherry UniversityPuducherryIndia

This paper introduces a new family of distributions defined in terms of quantile *** quantile function introduced here is the sum of quantile functions of life time distributions called Burr Ⅲ and *** distributional characteristics and reliability properties are included in the *** of Least Square and Method of L-moments are applied to estimate the parameters of the *** real life data sets are used to illustrate the performance of the model.

关键词： Weibull distribution Burr III distribution quantile density function quantile function hazard quantile function L-moments

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