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 Non-destructive silkworm pupa gender classification with X-ray images using ensemble learning Subject The topic of the resource AdaBoost; Gender classification; Machine learning; Sericulture; Stratified k-fold cross-validation Description An account of the resource Sericulture is the process of cultivating silkworms for the production of silk. High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers. One of the possibilities to overcome this issue is by separating male and female cocoons before extracting silk fibers from the cocoons as male cocoon silk fibers are finer than females. This study proposes a method for the classification of male and female cocoons with the help of X-ray images without destructing the cocoon. The study used popular single hybrid varieties FC1 and FC2 mulberry silkworm cocoons. The shape features of the pupa are considered for the classification process and were obtained without cutting the cocoon. A novel point interpolation method is used for the computation of the width and height of the cocoon. Different dimensionality reduction methods are employed to enhance the performance of the model. The preprocessed features are fed to the powerful ensemble learning method AdaBoost and used logistic regression as the base learner. This model attained a mean accuracy of 96.3% for FC1 and FC2 in cross-validation and 95.3% in FC1 and 95.1% in FC2 for external validation. 2022 The Authors Creator An entity primarily responsible for making the resource Thomas S.; Thomas J. Source A related resource from which the described resource is derived Artificial Intelligence in Agriculture, Vol-6, pp. 100-110. Publisher An entity responsible for making the resource available KeAi Communications Co. 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/10.1016/j.aiia.2022.08.001" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.aiia.2022.08.001</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135823686&amp;doi=10.1016%2Fj.aiia.2022.08.001&amp;partnerID=40&amp;md5=e8655d0b612b88b36fc148b5550a0d60" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135823686&amp;doi=10.1016%2fj.aiia.2022.08.001&amp;partnerID=40&amp;md5=e8655d0b612b88b36fc148b5550a0d60</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 25897217 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 Thomas S., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India; Thomas J., Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India