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 Articles Article Faculty Publications -Articles 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 Analysis and prediction of seed quality using machine learning Subject The topic of the resource Agriculture; Classification; Convolution neural network; Prediction; Seed quality Description An account of the resource The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecast seed quality is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, we have tried to create a prediction model that uses machine learning algorithms to forecast seed quality, leading to high crop yield and high-quality harvests. For precise seed categorization, this model was created using convolutional neural networks and trained using the seed dataset. Using data that can be used to forecast the future, this model is used to learn about whether the seeds are of premium quality, standard quality, or regular quality. While testing data are employed in the algorithms predictive analytics, training data and validation data are used for categorization reasons. Thus, by examining the training accuracy of the convolution neural network (CNN) model and the prediction accuracy of the algorithm, the projects primary goal is to develop the best method for the more accurate prediction of seed quality. 2023 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Srinivasaiah R.; Meenakshi; Channegowda R.H.; Jankatti S.K. Source A related resource from which the described resource is derived International Journal of Electrical and Computer Engineering, Vol-13, No. 5, pp. 5770-5781. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijece.v13i5.pp5770-5781" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijece.v13i5.pp5770-5781</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164340756&amp;doi=10.11591%2Fijece.v13i5.pp5770-5781&amp;partnerID=40&amp;md5=b22502a1e4425b0e908df5a7e4101444" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164340756&amp;doi=10.11591%2fijece.v13i5.pp5770-5781&amp;partnerID=40&amp;md5=b22502a1e4425b0e908df5a7e4101444</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 20888708 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 Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Srinivasaiah R., Department of Computer Science and Engineering, CHRIST Deemed to be University, Bengaluru, India; Meenakshi, Department of Computer Science and Engineering, RNS Institute of Technology, Bengaluru, India; Channegowda R.H., Department of Electronics and Communication, Dayananda Sagar Academy of Technology and Management, Bengaluru, India; Jankatti S.K., Department of Computer Science and Engineering, Dayananda Sagar University, Bengaluru, India