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 A multi-scale and rotation-invariant phase pattern (MRIPP) and a stack of restricted Boltzmann machine (RBM) with preprocessing for facial expression classification Subject The topic of the resource Classification; Emotion; Feature; Pattern; Texton Description An account of the resource In facial expression recognition applications, the classification accuracy decreases because of the blur, illumination and localization problems in images. Therefore, a robust emotion recognition technique is needed. In this work, a Multi-scale and Rotation-Invariant Phase Pattern (MRIPP) is proposed. The MRIPP extracts the features from facial images, and the extracted patterns are blur-insensitive, rotation-invariant and robust. The performance of classification algorithms like Fisher faces, Support Vector Machine (SVM), Extreme Learning Machine (ELM), Convolutional Neural Network (CNN) and Deep Neural Network (DNN) are analyzed. In order to reduce the time for classification, an OPTICS-based pre-processing of the features is proposed that creates a non-redundant and compressed training set to classify the test set. Ten-fold cross validation is used in experimental analysis and the performance metric classification accuracy is used. The proposed approach has been evaluated with six datasets Japanese Female Facial Expression (JAFFE), Cohn Kanade (CK +), Multi- media Understanding Group (MUG), Static Facial Expressions in the Wild (SFEW), Oulu-Chinese Academy of Science, Institute of Automation (Oulu-CASIA) and ManMachine Interaction (MMI) datasets to meet a classification accuracy of 98.2%, 97.5%, 95.6%, 35.5%, 87.7% and 82.4% for seven class emotion detection using a stack of Restricted Boltzmann Machines(RBM), which is high when compared to other latest methods. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Creator An entity primarily responsible for making the resource Alphonse A.S.; Shankar K.; Jeyasheela Rakkini M.J.; Ananthakrishnan S.; Athisayamani S.; Robert Singh A.; Gobi R. Source A related resource from which the described resource is derived Journal of Ambient Intelligence and Humanized Computing, Vol-12, No. 3, pp. 3447-3463. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s12652-020-02517-7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s12652-020-02517-7</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091149784&amp;doi=10.1007%2Fs12652-020-02517-7&amp;partnerID=40&amp;md5=d0695d05c8141a6a5bcea9550fab114a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091149784&amp;doi=10.1007%2fs12652-020-02517-7&amp;partnerID=40&amp;md5=d0695d05c8141a6a5bcea9550fab114a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18685137 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 Alphonse A.S., Department of Information Technology, Ponjesly College of Engineering, Nagercoil, India; Shankar K., Department of Computer Applications, Alagappa University, Karaikudi, India; Jeyasheela Rakkini M.J., School of Computing, Sastra Deemed To Be University, Thanjavur, India; Ananthakrishnan S., School of Computing, Sastra Deemed To Be University, Thanjavur, India; Athisayamani S., School of Computing, Sastra Deemed To Be University, Thanjavur, India; Robert Singh A., School of Computing, Kalasalingam Academy of Research and Education, Anand Nagar, India; Gobi R., Department of Computer Science, Christ University, Bengalore, India