.png){kind=icon}
返回
Contextual emotion detection in images using deep learning
.png){kind=icon}
OA
AI
DOI：10.3389/frai.2024.1386753.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Introduction Computerized sentiment detection, based on artificial intelligence and computer vision, has become essential in recent years. Thanks to developments in deep neural networks, this technology can now account for environmental, social, and cultural factors, as well as facial expressions. We aim to create more empathetic systems for various purposes, from medicine to interpreting emotional interactions on social media.Methods To develop this technology, we combined authentic images from various databases, including EMOTIC (ADE20K, MSCOCO), EMODB_SMALL, and FRAMESDB, to train our models. We developed two sophisticated algorithms based on deep learning techniques, DCNN and VGG19. By optimizing the hyperparameters of our models, we analyze context and body language to improve our understanding of human emotions in images. We merge the 26 discrete emotional categories with the three continuous emotional dimensions to identify emotions in context. The proposed pipeline is completed by fusing our models.Results We adjusted the parameters to outperform previous methods in capturing various emotions in different contexts. Our study showed that the Sentiment_recognition_model and VGG19_contexte increased mAP by 42.81% and 44.12%, respectively, surpassing the results of previous studies.Discussion This groundbreaking research could significantly improve contextual emotion recognition in images. The implications of these promising results are far-reaching, extending to diverse fields such as social robotics, affective computing, human-machine interaction, and human-robot communication.
Keyword:
computer vision
contextual recognition
EMOTIC
emotion recognition
body language
human-robot communication
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
F
IF:
4.7
论文数:
2.5K
被引数:
4.4K
机构
引用论文
分享收藏PACC: A platoon-based adaptive cruise control strategy based on leader-following information topology to mitigate traffic oscillations under CAV environmentPACC：一种基于领导者-跟随者信息拓扑的编队自适应巡航控制策略，用于在CAV环境下缓解交通振荡
PREAI
分享收藏Unravelling the biosynthesis of pyriculol in the rice blast fungus Magnaporthe oryzae.png)
Microbiology
OAAI
MicrobiologyIF0
OAAI分享收藏
查看更多内容