Beyond Basic Emotions: Deep Neural Networks for Compound Facial Expression Detection

DOI

10.2991/978-94-6239-713-2_15How to use a DOI?

Keywords

Emotion Detection; Basic & complex emotion detection; Machine Learning (ML); Deep Learning (DL); Convolutional Neural Network (CNN)

Abstract

In this research, a fundamental method for deep learning-based emotion identification from facial photographs is presented. Happiness, sorrow, surprise, rage, and other basic emotions are automatically extracted and classified using a Convolutional Neural Network (CNN) model. The model's performance in emotion identification tasks is assessed after it has been trained on a dataset of photos. The CNN model successfully captures facial features for categorization and achieves adequate accuracy, according to experimental data. A fundamental framework for emotion recognition is provided by this work, which can be expanded with more sophisticated methods for better results. According to experimental data, our sequential CNN-based approach performs more accurately than conventional machine learning models, especially when detecting ambiguous or insignificant emotional cues. The results demonstrate how CNNs can improve emotion detection models for social media applications and provide more in-depth understanding of online user behavior, content engagement, and social dynamics with approximately 98% accuracy.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Shabanam Bano
AU  - Pawan Bhambu
PY  - 2026
DA  - 2026/06/25
TI  - Beyond Basic Emotions: Deep Neural Networks for Compound Facial Expression Detection
BT  - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
PB  - Atlantis Press
SP  - 207
EP  - 218
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-713-2_15
DO  - 10.2991/978-94-6239-713-2_15
ID  - Bano2026
ER  -