清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Facial Expression Recognition Using YOLO

面部表情识别 计算机科学 面部识别系统 面部表情 人工智能 模式识别(心理学) 计算机视觉
作者
K C Tejaswi,D Mokshith,Sai Pradeep E,Ch Mahesh Kumar,Manoj Kumar K
标识
DOI:10.1109/rmkmate59243.2023.10369028
摘要

This study presents a facial expression recognition system that utilizes the You Only Look Once (YOLO) object detection framework. The system leverages the capabilities of YOLO to detect and classify facial expressions accurately and efficiently.The main objective is to achieve efficient and real-time detection and classification of facial expressions. By utilizing the YOLO framework's object detection capabilities, the system can accurately locate and extract facial regions of interest for subsequent analysis. To train the system, a large dataset of labeled facial images representing various expressions, such as happiness, sadness, anger, fear, surprise, and neutral, is utilized. Deep learning techniques, including convolutional neural networks (CNNs), are employed to optimize the modified YOLO network's parameters, enhancing expression recognition accuracy.Experimental evaluation on benchmark facial expression datasets demonstrates the effectiveness and efficiency of the proposed YOLO-based facial expression recognition system. It surpasses existing approaches in terms of both accuracy and real-time performance, making it highly suitable for practical applications. The proposed facial expression recognition system based on the YOLO object detection framework demonstrates the capability to detect and classify facial expressions in real-time. This advancement opens up new possibilities in fields such as emotion detection, human-computer interaction, and affective computing. The approach not only improves accuracy but also addresses the crucial requirement for real-time processing, which is essential for various real-world applications. By leveraging the advantages of the YOLO framework, the system achieves a good balance between accuracy and speed, enabling efficient and effective facial expression analysis. With its promising results, the YOLO-based facial expression recognition system holds great potential for advancing fields that rely on accurate and real-time emotion analysis..

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
6秒前
linllll发布了新的文献求助10
12秒前
爆米花应助义气的导师采纳,获得10
13秒前
EE完成签到,获得积分10
28秒前
44秒前
无情幻巧完成签到,获得积分10
44秒前
yyl19930705完成签到,获得积分10
46秒前
Nina发布了新的文献求助10
49秒前
51秒前
大大大忽悠完成签到 ,获得积分10
1分钟前
科研通AI6.2应助linllll采纳,获得10
1分钟前
糟糕的问丝完成签到,获得积分10
1分钟前
愤怒的若颜完成签到,获得积分10
2分钟前
wangfaqing942完成签到 ,获得积分10
2分钟前
桑稚完成签到 ,获得积分10
2分钟前
Sunny完成签到,获得积分10
2分钟前
故意的梦琪完成签到,获得积分10
2分钟前
2分钟前
2分钟前
linllll发布了新的文献求助10
3分钟前
老石完成签到 ,获得积分10
3分钟前
Dino完成签到 ,获得积分10
3分钟前
3分钟前
展会恩完成签到,获得积分10
3分钟前
英俊的傲珊完成签到,获得积分10
3分钟前
manman完成签到 ,获得积分10
3分钟前
科研通AI2S应助宋玮采纳,获得10
4分钟前
酷波er应助科研通管家采纳,获得20
4分钟前
我是老大应助YMW采纳,获得10
4分钟前
4分钟前
宋玮发布了新的文献求助10
4分钟前
威武的若山完成签到,获得积分10
4分钟前
霸气侧漏完成签到,获得积分10
4分钟前
FashionBoy应助pigff采纳,获得10
4分钟前
5分钟前
孤独剑完成签到 ,获得积分10
5分钟前
pigff发布了新的文献求助10
5分钟前
苗条的采梦完成签到,获得积分10
5分钟前
干净的醉蝶完成签到,获得积分10
6分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
化工安全与环保 1000
Autoparametric Resonance in Mechanical Systems 1000
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults 700
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7656604
求助须知:如何正确求助?哪些是违规求助? 9227260
关于积分的说明 19828813
捐赠科研通 7222919
什么是DOI,文献DOI怎么找? 3280326
关于科研通互助平台的介绍 2440582
邀请新用户注册赠送积分活动 2280172