基于级联卷积神经网络的疲劳检测

为了诊断热核聚变等离子体状态,研制了用于热 斑区等离子体诊断用的新型X射线光谱仪,能够同 时探测X射线光谱与聚爆靶图像信息。光谱检测功能由4块椭圆晶体分析器实现,材料分别 为α-石英(1010)、 α-石英(2023)、α-石英(1011)和Si(111),几乎能够覆盖2~20 keV能带范围内的X射线特 征光谱。光谱检测 结构为光源位于椭圆的一个焦点,其辐射光谱经过椭圆反射聚焦于椭圆另一焦点,由X射线 成像板(IP)接收。图 像检测功能由分幅相机匹配小孔阵列成像完成,理想状态能够得到20 幅不同时间的聚爆靶图像。在谱仪与 聚爆靶之间的调整台上设置厚为60μm的Be膜,以保护针孔与晶体避 免聚爆溅射碎片破坏。在中物院“神光- Ⅱ”升级装置上进行了打靶实验,获取了X射线光谱与聚爆靶图像信号。分析了光谱及图像 信息,并针对光谱 仪漏光问题改进了光谱仪结构,最后在神光-Ⅲ原型装置上进行了验证实验并获得比较理想 的图像信号,信噪比(SNR)数据达到15dB。

Fatigue detection based on cascade convolutional neural network

In this paper,a new fatigue detection method based on cascade convolutional neur al network (CNN) structure is proposed.Firstly,for learning the eye features,the first-level network is trained to classify the eye and non-ey e regions.The eye region is extracted by the feature maps of the first-level network.Then,the eye images are sent to the nex t network for the eye feature point detection.The eye opening degree is computed to estimate the eye states o f the subject and construct the model of fatigue detection.Finally,whether fatigue driving or not is judged by t he time series of eye states in multi-consecutive frames.At the detection error of 5%,the average detection acc uracy of eye feature points is 93.10% and the highest detection accuracy of a single point is 97.14%.The experi mental results of our method show that the detected eye states based on the proposed method are obviously dif ferent in awake and fatigue states,which proves the proposed method is effective and has a better application prospect.