Citation

Ho, Jia Jun and Khoh, Wee How and Pang, Ying Han and Yap, Hui Yen and Lim, Alvin Fang Chuen (2026) AI Creation of Facial Expression Database for Advanced Emotion Recognition Using Diffusion Model and Pre-Trained CNN Models. Applied Sciences, 16 (6). p. 2769. ISSN 2076-3417

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Abstract

With applications in psychology, security, and human–computer interaction, facial expression recognition (FER) has become an essential tool for non-verbal communication. Current research often categorizes expressions into micro- and macro-types, yet existing datasets suffer from inconsistent labelling for classes, limited diversity of the databases, and insufficient scale for the currently available datasets. To address these gaps, this work proposes a novel framework combining the diffusion model with pre-trained CNNs. Leveraging original images from established datasets, CASME II, we generate synthetic facial expressions to augment training data, mitigating bias and inconsistency. The synthetic dataset is evaluated using ResNet 50, VGG16 and Inception V3 architectures. Inception V3 trained on the proposed AI-generated dataset and tested using CASME II, VGG-16 with data augmentation applied is trained on CASME II and tested on the proposed AI-generated dataset, and Inception V3 with 30% freezing layers method is trained on the proposed AI-generated dataset and tested using CASME II. These all successfully achieved state-ofthe-art performance. The data augmentation and freezing layers approaches significantly improved the performance of the models. Our proposed approaches achieved state-ofthe-art performance and outperformed most of the existing state-of-the-art approaches benchmarked in this study.

Item Type:	Article
Uncontrolled Keywords:	Convolutional neural networks, deep learning
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Information Science and Technology (FIST) Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Apr 2026 09:09
Last Modified:	07 Apr 2026 02:19
URII:	http://shdl.mmu.edu.my/id/eprint/15680

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