A comparative analysis of hyperparameter effects on CNN architectures for facial emotion recognition

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: A comparative analysis of hyperparameter effects on CNN architectures for facial emotion recognition
Συγγραφείς: Grillo, Benjamin, Kontorinaki, Maria, Sammut, Fiona, 14th International Conference on Pattern Recognition Applications and Methods ICPRAM
Στοιχεία εκδότη: SciTePress
Έτος έκδοσης: 2025
Συλλογή: University of Malta: OAR@UM / L-Università ta' Malta
Θεματικοί όροι: Human face recognition (Computer science), Emotion recognition -- Data processing, Pattern recognition systems -- Data processing, Neural networks (Computer science), Human-computer interaction, Image processing -- Data processing
Περιγραφή: This study investigates facial emotion recognition, an area of computer vision that involves identifying human emotions from facial expressions. It approaches facial emotion recognition as a classification task using labelled images. More specifically, we use the FER2013 dataset and employ Convolutional Neural Networks due to their capacity to efficiently process and extract hierarchical features from image data. This research utilises custom network architectures to compare the impact of various hyperparameters - such as the number of convolutional layers, regularisation parameters, and learning rates - on model performance. Hyperparameters are systematically tuned to determine their effects on accuracy and overall performance. According to various studies, the best-performing models on the FER2013 dataset surpass human-level performance, which is between 65% and 68%. While our models did not achieve the best-reported accuracy in literature, the findings still provide valuable insights into hyperparameter optimisation for facial emotion recognition, demonstrating the impact of different configurations on model performance and contributing to ongoing research in this area. ; peer-reviewed
Τύπος εγγράφου: conference object
Γλώσσα: English
Relation: https://www.um.edu.mt/library/oar/handle/123456789/133206
DOI: 10.5220/0013146900003905
Διαθεσιμότητα: https://www.um.edu.mt/library/oar/handle/123456789/133206
https://doi.org/10.5220/0013146900003905
Rights: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.
Αριθμός Καταχώρησης: edsbas.8651EE35
Βάση Δεδομένων: BASE