Separable convolutional neural networks for facial expressions recognition

Author:

Chowanda AndryORCID

Abstract

AbstractSocial interactions are important for us, humans, as social creatures. Emotions play an important part in social interactions. They usually express meanings along with the spoken utterances to the interlocutors. Automatic facial expressions recognition is one technique to automatically capture, recognise, and understand emotions from the interlocutor. Many techniques proposed to increase the accuracy of emotions recognition from facial cues. Architecture such as convolutional neural networks demonstrates promising results for emotions recognition. However, most of the current models of convolutional neural networks require an enormous computational power to train and process emotional recognition. This research aims to build compact networks with depthwise separable layers while also maintaining performance. Three datasets and three other similar architectures were used to be compared with the proposed architecture. The results show that the proposed architecture performed the best among the other architectures. It achieved up to 13% better accuracy and 6–71% smaller and more compact than the other architectures. The best testing accuracy achieved by the architecture was 99.4%.

Publisher

Springer Science and Business Media LLC

Subject

Information Systems and Management,Computer Networks and Communications,Hardware and Architecture,Information Systems

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Demystifying Mental Health by Decoding Facial Action Unit Sequences;Big Data and Cognitive Computing;2024-07-09

2. Structural self-contrast learning based on adaptive weighted negative samples for facial expression recognition;The Visual Computer;2024-04-15

3. Exploring the Impact of ‘Emotion-Recognition-AI’ on Consumer Trust and Satisfaction;2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS);2024-02-24

4. Identification of Mood in Early Childhood with Face Recognition;2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA);2023-10-04

5. Implementing Vision Transformer to Model Emotions Recognition from Facial Expressions;2023 4th International Conference on Artificial Intelligence and Data Sciences (AiDAS);2023-09-06

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