战斗部破片群运动参数对弹药毁伤威力评估具有重要的意义。针对破片尺寸较小、背景信息复杂以及破片数据样本少导致的破片检测精度较低的问题,本文提出一种YOLOv5-FD的战斗部破片群目标检测方法。首先,在网络输出端增加微小目标检测层,...战斗部破片群运动参数对弹药毁伤威力评估具有重要的意义。针对破片尺寸较小、背景信息复杂以及破片数据样本少导致的破片检测精度较低的问题,本文提出一种YOLOv5-FD的战斗部破片群目标检测方法。首先,在网络输出端增加微小目标检测层,将原始的三尺度改为四尺度,并在特征融合网络中引入内容感知特征重组(Content Aware ReAssembly of Features,CARAFE)上采样模块替换原有的最近邻插值上采样,减少小目标特征信息损失,提高弱小破片的提取能力。其次,在特征提取网络引入坐标注意力模块(Coordinate Attention,CA),加强对破片特征的提取,弱化背景信息,抑制复杂背景的干扰。最后,在模型训练过程中引入模型不可知元学习方法(Model Agnostic Meta Learning,MAML),达到仅用小样本破片数据集实现较高的检测性能。实验结果表明,YOLOv5-FD破片检测算法在自制破片数据集中,精确率达到了90.5%,召回率达到了85.4%,平均精度mAP_0.5达到了88.2%,与原始YOLOv5s算法相比分别提高了7.1%,7.9%和7.5%,有效提高了破片目标检测准确性。展开更多
With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network str...With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network stream to perform packet processing at a semantic level above the network layer. This paper presents an efficient TCP stream reassembly mechanism for real-time processing of high-speed network traffic. By analyzing the characteristics of network stream in high-speed network and TCP connection establishment process, several polices for designing the reassembly mechanism are built. Then, the reassembly implementation is elaborated in accordance with the policies. Finally, the reassembly mechanism is compared with the traditional reassembly mechanism by the network traffic captured in a typical gigabit gateway. Experiment results illustrate that the reassembly mechanism is efficient and can satisfy the real-time property requirement of traffic analysis system in high-speed network.展开更多
Myelinated axons of the peripheral and central nervous system（PNS＆CNS）are divided into molecularly distinct excitable domains,including the axon initial segment（AIS）and nodes of Ranvier.The AIS is composed of a d...Myelinated axons of the peripheral and central nervous system（PNS＆CNS）are divided into molecularly distinct excitable domains,including the axon initial segment（AIS）and nodes of Ranvier.The AIS is composed of a dense network of cytoskeletal proteins,cell adhesion molecules,and voltage gated ion channels and is located at the proximal most region of the axon（Koleand Stuart, 2012）.展开更多
在自动驾驶场景中,针对复杂背景对车辆和行人检测目标影响大、小目标检测精度不高的问题,提出一种基于内容感知重组特征和自适应融合的YOLOv5(content-aware reassembly of feature and adaptive fusion YOLOv5,CRAF-YOLOv5)车辆及行人...在自动驾驶场景中,针对复杂背景对车辆和行人检测目标影响大、小目标检测精度不高的问题,提出一种基于内容感知重组特征和自适应融合的YOLOv5(content-aware reassembly of feature and adaptive fusion YOLOv5,CRAF-YOLOv5)车辆及行人检测算法。通过引入通道注意力机制形成多通道特征提取网络,增强复杂背景下目标特征的提取性能;在特征融合前段,通过内容感知重组特征进行上采样,并添加基于跳跃连接结构,强化浅层网络对小目标特征的表征能力;在特征融合后段,采用自适应权重融合方式学习不同尺度特征,实现深层和浅层特征的动态学习和深度融合。实验结果表明,该算法在BDD100K和KITTI数据集上车辆行人目标检测平均均值精度分别达到84.40%和93.35%,较YOLOv5基准算法分别提高了3.90%和0.45%。展开更多
随着电力调度脉冲编码调制(PCM)设备的逐步退运,电网公司将逐步采用光传输设备替代调度PCM设备。在设备更换的过渡期,存在大量光传输设备与PCM设备混用的情况。为解决电力调度传输网络中存在的E1与互联网协议(IP)分组业务转换难度大、...随着电力调度脉冲编码调制(PCM)设备的逐步退运,电网公司将逐步采用光传输设备替代调度PCM设备。在设备更换的过渡期,存在大量光传输设备与PCM设备混用的情况。为解决电力调度传输网络中存在的E1与互联网协议(IP)分组业务转换难度大、转换速率低的问题,提出了1种基于网络切片的IP over E1方法。首先,将要传输的数据打包成IP数据。然后,基于网络切片技术,将IP数据包切片后,封装成E1帧。在此基础上,通过E1链路进行数据传输,在接收端通过E1数据帧拆解完成IP数据包的重组发送。最后,将所提方法在某省电力公司进行实例运行,IP over E1转换准确率为99.86%。其结果验证了该方法的有效性。该方法可有效提高IP over E1转换速度和准确率。展开更多
文摘战斗部破片群运动参数对弹药毁伤威力评估具有重要的意义。针对破片尺寸较小、背景信息复杂以及破片数据样本少导致的破片检测精度较低的问题,本文提出一种YOLOv5-FD的战斗部破片群目标检测方法。首先,在网络输出端增加微小目标检测层,将原始的三尺度改为四尺度,并在特征融合网络中引入内容感知特征重组(Content Aware ReAssembly of Features,CARAFE)上采样模块替换原有的最近邻插值上采样,减少小目标特征信息损失,提高弱小破片的提取能力。其次,在特征提取网络引入坐标注意力模块(Coordinate Attention,CA),加强对破片特征的提取,弱化背景信息,抑制复杂背景的干扰。最后,在模型训练过程中引入模型不可知元学习方法(Model Agnostic Meta Learning,MAML),达到仅用小样本破片数据集实现较高的检测性能。实验结果表明,YOLOv5-FD破片检测算法在自制破片数据集中,精确率达到了90.5%,召回率达到了85.4%,平均精度mAP_0.5达到了88.2%,与原始YOLOv5s算法相比分别提高了7.1%,7.9%和7.5%,有效提高了破片目标检测准确性。
基金National High-Tech Research and Development Program of China (863 Program) (No.2007AA01Z309)
文摘With the continual growth of the variety and complexity of network crime means, the traditional packet feature matching cannot detect all kinds of intrusion behaviors completely. It is urgent to reassemble network stream to perform packet processing at a semantic level above the network layer. This paper presents an efficient TCP stream reassembly mechanism for real-time processing of high-speed network traffic. By analyzing the characteristics of network stream in high-speed network and TCP connection establishment process, several polices for designing the reassembly mechanism are built. Then, the reassembly implementation is elaborated in accordance with the policies. Finally, the reassembly mechanism is compared with the traditional reassembly mechanism by the network traffic captured in a typical gigabit gateway. Experiment results illustrate that the reassembly mechanism is efficient and can satisfy the real-time property requirement of traffic analysis system in high-speed network.
基金supported by National Institutes of Health Grants NS069688 and NS044916, TIRR Foundationthe Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
文摘Myelinated axons of the peripheral and central nervous system（PNS＆CNS）are divided into molecularly distinct excitable domains,including the axon initial segment（AIS）and nodes of Ranvier.The AIS is composed of a dense network of cytoskeletal proteins,cell adhesion molecules,and voltage gated ion channels and is located at the proximal most region of the axon（Koleand Stuart, 2012）.
文摘在自动驾驶场景中,针对复杂背景对车辆和行人检测目标影响大、小目标检测精度不高的问题,提出一种基于内容感知重组特征和自适应融合的YOLOv5(content-aware reassembly of feature and adaptive fusion YOLOv5,CRAF-YOLOv5)车辆及行人检测算法。通过引入通道注意力机制形成多通道特征提取网络,增强复杂背景下目标特征的提取性能;在特征融合前段,通过内容感知重组特征进行上采样,并添加基于跳跃连接结构,强化浅层网络对小目标特征的表征能力;在特征融合后段,采用自适应权重融合方式学习不同尺度特征,实现深层和浅层特征的动态学习和深度融合。实验结果表明,该算法在BDD100K和KITTI数据集上车辆行人目标检测平均均值精度分别达到84.40%和93.35%,较YOLOv5基准算法分别提高了3.90%和0.45%。
文摘随着电力调度脉冲编码调制(PCM)设备的逐步退运,电网公司将逐步采用光传输设备替代调度PCM设备。在设备更换的过渡期,存在大量光传输设备与PCM设备混用的情况。为解决电力调度传输网络中存在的E1与互联网协议(IP)分组业务转换难度大、转换速率低的问题,提出了1种基于网络切片的IP over E1方法。首先,将要传输的数据打包成IP数据。然后,基于网络切片技术,将IP数据包切片后,封装成E1帧。在此基础上,通过E1链路进行数据传输,在接收端通过E1数据帧拆解完成IP数据包的重组发送。最后,将所提方法在某省电力公司进行实例运行,IP over E1转换准确率为99.86%。其结果验证了该方法的有效性。该方法可有效提高IP over E1转换速度和准确率。
