使用 DNN 制作面部图像字幕

Vijayalakshmi B
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引用次数: 0

摘要

面部分析包括情感、年龄和性别检测,在人机交互、商业、安全和健康等各种应用领域都显示出潜力。本研究深入探讨了用于面部情绪、年龄和性别检测的深度神经网络(DNN)模型的开发和评估。我们的模型利用卷积神经网络(CNN)架构,在不同任务的数据集上进行训练,证明能有效预测面部特征。需求评估的准确率为 X%,年龄估计的边际误差(MAE)为 Y 年,性别分类的准确率为 Z%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FACIAL IMAGE CAPTIONING USING DNN
Facial analysis, encompassing emotion, age, and gender detection, shows potential in various applications such as human-computer interaction, business, security, and health. This study delves into the development and evaluation of a deep neural network (DNN) model for facial emotion, age, and gender detection. Utilizing a convolutional neural network (CNN) architecture trained on diverse datasets for each task, our model proves effective in predicting facial features. The accuracy of needs assessment is X%, the marginal error (MAE) of age estimation is Y years, and the accuracy of gender classification is Z%.
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