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 Faculty Publications 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/. Creator An entity primarily responsible for making the resource Raji, V.; Maheswari, S.; Kanmani, P.; Kavin, K.S.; Janice, J. Benisha; Lawrence, Jinsha Title A name given to the resource EEG Emotion Recognition Using PSO-Based Feature Selection and Convolutional Neural Networks Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 Global Conference in Emerging Technology, GINOTECH 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/GINOTECH63460.2025.11077080" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/GINOTECH63460.2025.11077080</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013619510?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013619510?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Raji V., S.K.P. Engineering College, Department of Information Technology, Tiruvannamalai, India; Maheswari S., Nandha Engineering College, Department of Computer Science and Engineering(IoT), Tamilnadu, Erode, 638052, India; Kanmani P., Christ University, School of Engineering and Technology, Department of Computer Science and Engineering, Kengeri Campus, Bangalore, 560074, India; Kavin K.S., Government College of Engineering, Department of Electrical and Electronics Engineering, Tamil Nadu, Tirunelveli, India; Janice J.B., Mar Ephraem College of Engineering and Technology, Department of Computer Science and Engineering, Elavuvilai, India; Lawrence J., Karpagam Academy of Higher Education (Deemed to be University), Department of Computer Science and Engineering, Tamil Nadu, Coimbatore, India Description An account of the resource EEG signals have become a promising source for emotion recognition due to their ability to capture the brain's electrical activity connected with different emotional conditions. In this work, a novel approach is proposed that integrates Particle Swarm Optimization (PSO)-based feature selection with Convolutional Neural Networks (CNNs) for improved EEG emotion classification. The method with the preprocessing of a notch filter to eliminate noise and enhance the quality of the EEG signals. Key features, including Magnitude Squared Coherence Estimate (MSCE) and Power Spectral Density (PSD), are extracted to capture essential frequency-domain information. PSO is employed to optimize the selection of features, reducing dimensionality while preserving the most relevant and informative attributes for emotion recognition. The optimized feature was subsequently passed to a CNN classifier, which improves the model's capability to accurately differentiate between different emotional states. This study is implemented using Python software to analyze emotion, and the effectiveness of the proposed approach is assessed using the EEG Brainwave dataset. Experimental results demonstrate that the proposed approach delivers an accuracy of 92.6% and a precision of 91%, highlighting its effectiveness in real-time, high-precision emotion recognition from EEG data. 2025 IEEE. Subject The topic of the resource and EEG Emotion; CNN; MSCE; PSD; PSO Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833150775-6; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online