Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Identification Of Quality Of Tea Leaves By Using Artificial Intelligence Techniques: A Review Description An account of the resource This paper summarizes the outcome of the survey carried out for quality identification of a tea leaf and eventually price prediction. Quality identification can allow to categorizing leaf in different grades, which helps the buyer and seller to acquire suitable quality to their need. Price prediction is an important feature, which can bring certainty at price and farmers can be benefitted more for their good quality. Additionally, if the leaf disease is identified at the initial stage that would also allow farmers to timely resolve the concerned issues and save their corps. In the field of agriculture, this has been always a research area to identify and predict the quality of tea leaves. Various artificial intelligence techniques are hot topics in the field of recognition and their effective combination can not only solve the problem but also enhance recognition accuracy. Therefore, there is an imminent need for a detailed survey on compiling techniques used for the identification of different varieties of tea plants. In this research, we aim to propose a review of the various techniques which can be utilized for determining the quality and price prediction. The Survey is hybrid with a combination of different artificial techniques, which is a suitable approach to target effective tea leaf identification. Further for the classification of tea leaf images, various algorithms can be combined as well to obtain better results and different algorithms can be used for feature extraction based on texture extraction, color extraction, and shape extraction. The Electrochemical Society Creator An entity primarily responsible for making the resource Gaba I.; Ramamurthy B. Source A related resource from which the described resource is derived ECS Transactions, Vol-107, No. 1, pp. 2053-2071. Publisher An entity responsible for making the resource available Institute of Physics Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1149/10701.2053ecst" target="_blank" rel="noreferrer noopener">https://doi.org/10.1149/10701.2053ecst</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130516574&amp;doi=10.1149%2F10701.2053ecst&amp;partnerID=40&amp;md5=cde4ef08312766e6c2b1638015555e9d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130516574&amp;doi=10.1149%2f10701.2053ecst&amp;partnerID=40&amp;md5=cde4ef08312766e6c2b1638015555e9d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 19386737; ISBN: 978-160768539-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gaba I., Department of Computer Science, Christ (Deemed to be University), Bangalore, India; Ramamurthy B., Department of Computer Science, Christ (Deemed to be University), Bangalore, India