TY -的A2 Doulamis Anastasios d . AU -古普塔,Sandeep Kumar盟——Yesuf Seid•盟——将近城门,Neeta PY - 2022 DA - 2022/03/17 TI -实时性别识别青少年和成人面孔SP - 1503188六世- 2022 AB -人脸性别识别是一个至关重要的研究课题由于其全面的用例,包括人口性别调查显示,游客形象识别、有针对性的广告,访问控制、安全和监视闭路电视。对于这些实时应用程序,一个人的脸可以从相机面向任何角度轴,和任何年龄段的人都可以,包括青少年。孩子的脸由不成熟的颅面特征点的纹理和边缘相比,一个成年人的脸,使得它很难识别性别使用孩子的脸。现实世界面临捕获在一个不受约束的环境中进行正确的性别预测系统更复杂的识别由于取向。这些因素降低现有最先进的模型的准确性发达到目前为止实时人脸性别预测。介绍了新奇人脸性别识别的青少年,成年人,unconstrained-oriented面孔。进步校准网络(PCN)检测模型的旋转不变的脸。然后,伽柏滤波器应用于提取独特的边缘和纹理特征的检测到的脸。伽柏过滤器和光照不变产生纹理和边缘特征冗余特性系数较大的尺寸。伽柏有缺点,如冗余和一个大维度提出解决的meanDWT特性优化方法,优化系统的准确性,大小的模型,计算时间。 The proposed feature engineering model is classified with different classifiers such as Naïve Bayes, Logistic Regression, SVM with linear, and RBF kernel. Its results are compared with the state-of-the-art techniques; detailed experimental analysis is presented and concluded to support the argument. We also present a review of approaches based on conventional and deep learning methods with their pros and cons for facial gender recognition on different datasets available for facial gender recognition. SN - 1687-5265 UR - https://doi.org/10.1155/2022/1503188 DO - 10.1155/2022/1503188 JF - Computational Intelligence and Neuroscience PB - Hindawi KW - ER -