A new recognition algorithm of small moving target based on multi-feature fusion is presented.
提出一种新的基于多特征融合的弱小运动目标识别方法。
Fuzzy integral is an effective decision level fusion method for target recognition.
模糊积分是一种有效的决策层融合目标识别方法。
This dissertation points out the most pivotal problems in data fusion, i. e., data association, state estimation and target recognition, which are investigated in depth.
本文指出了数据融合中最为关键的几个问题——数据关联、状态估计和目标识别并围绕它们进行了深入的研究。
Target recognition is an important component of data fusion technology and also be a key problem in military affairs research field.
目标识别是数据融合技术的一个重要组成部分，也是军事技术研究领域中的一个重要课题。
As to sea image, the variance feature of region of interest and the luminance contrast feature between target and background are used to fusion recognition.
对于海面图像，分别采用感兴趣舰船目标区域的方差值、目标和背景亮度对比度这两个特征对目标进行融合识别。
We use a parallel and with feedback fusion system architecture, cascade D-S evidence theory to be fusion algorithm. Finally, a graphic target recognition system is realized.
系统采用有反馈的全并行融合系统结构，以分级式d S证据推理为数据融合算法，最终实现一个图形化的目标识别系统。
Then, a fusion recognition method was proposed using polarized information of target under the high range resolution fully polarized radar.
而后，基于全极化高分辨雷达，提出了一种利用目标极化信息一维距离像的综合识别方法。
A fuzzy counter propagation neural network (FCPN) based data fusion approach and a modified fuzzy counter propagation neural network (MFCPN) fusion architecture are proposed for target recognition.
针对数据融合和目标识别的特点，提出了基于模糊对向传播网络的融合目标识别方法和改进的模糊对向传播网络(MFCPN)融合结构。
Aiming at the target recognition problem of multi-sensor with multiple characteristic indexes, a new fusion method data is proposed.
针对具有多个特征指标的多传感器目标识别问题，提出了一种新的融合方法。
In order to meet the needs of target recognition, the data fusion technology of multi-sensor has become a research hotspot.
为了满足目标识别的需要，多传感器的数据融合技术已经成为研究的热点。
Decision templates is an intuitive decision level fusion scheme for target recognition.
决策模板法是一种直观的决策层融合目标识别方法。
Image registration is an important step of image fusion, change detection and target recognition in remote-sensing applications.
图像配准是图像融合、变化检测、目标识别等遥感应用中的重要步骤。
In this paper, new synthetic aperture radar (SAR) image target recognition approach based on multiple views decision fusion is presented.
提出了一种基于多方位角图像决策融合的合成孔径雷达(SAR)图像目标识别方法。
Data fusion of an integrated multisensor system is an advanced technology for target detection, recognition and tracking.
多传感器组合系统数据融合技术是当代探测、识别领域的一项新技术。
A moving target recognition method is proposed in this paper, which is based on multi-features fusion.
本文基于多特征融合，提出了一种运动目标识别方法。
The feature fusion of image has more and more important applications, such as in target recognition, medical treatment and biology feature recognition.
而图像融合中的特征级融合在目标识别、医疗诊断以及生物特征识别等领域有着越来越重要的作用。
Finally, the target recognition example based on this fusion model shows that this method is efficient and correct.
文末的目标识别实例表明了该方法的有效性和实用性。
Image fusion applied for target recognition should be modeling for each different task.
面向目标识别的图像融合需依据不同的目标任务建立不同的融合模型。
Study on Intelligent Data Fusion of Target Recognition in a Complex Environment;
决策模板法是一种直观的决策层融合目标识别方法。
Study on Intelligent Data Fusion of Target Recognition in a Complex Environment;
决策模板法是一种直观的决策层融合目标识别方法。
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