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3篇 您的检索式：作者名="Tripti Sharma"

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		题名	作者	年代	出处	被引量
	1	Distributed Differences Structures Underlie Gating between the Kin Channel KAT1 and the Kout Channel SKOR显示文摘	Janin Riedelsberger Tripti Sharma Wendy Gonzalez Pawel Gajdanowicz Samuel Elias Morales-Navarro Carlos Garcia-Mata Bernd Mueller-Roeber Fernando Danilo Gonzalez-Nilo Michael R. Blatt Ingo Dreyer	2010	Molecular Plant2010，3，1：	2
	2	Measuring the customer perceived service quality for life insurance services: An empirical investigation显示文摘	Masood H Siddiqui Tripti Ghosh Sharma	2012	International Business Research2012，3，3：	1
	3	MRMR Based Feature Vector Design for Efficient Citrus Disease Detection显示文摘In recent times,the images and videos have emerged as one of the most important information source depicting the real time scenarios.Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane.The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition.One of the application fields pertains to detection of diseases occurring in the plants,which are destroying the widespread fields.Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests.This is a tedious and time consuming process and does not suffice the accuracy levels.This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading.The digital images captured from the field’s forms the dataset which trains the machine learning models to predict the nature of the disease.The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images,appropriate segmentation methodology,feature vector development and the choice of machine learning algorithm.To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages.Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection.The training vector thus developed is capable of presenting the relationship between the feature values and the target class.In this article,a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed.The overall improvement in terms of accuracy is measured and depicted.	Bobbinpreet Sultan Aljahdali Tripti Sharma Bhawna Goyal Ayush Dogra Shubham Mahajan Amit Kant Pandit	2022	Computers, Materials & Continua2022，，9：	0

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