提出一种基于标记矫正的目标特征提取算法。
A target feature detecting algorithm based on label rectification is presented.
利用混沌理论对水下目标特征提取进行了研究。
Study on the pulsed feeding wire system for underwater welding;
本文着重研究基于高分辨率雷达视频回波的目标特征提取问题。
The target feature extraction about high resolution radar video echo is studied in this paper.
计算结果可用于目标特征提取、识别和分类,满足工程精度需求。
The result can meet engineering precision requirement and can be used for the target optical signature extraction, recognition and classification.
这些结论可以有效的指导实际的SARATR中的目标特征提取。
These conclusions provide a guideline for feature extraction in SAR ATR.
目标特征提取技术是深弹近炸引信系统中的一个重要功能模块,是引信系统成功识别目标的关键。
Target feature extraction plays an important role in the depth bomb fuze system, because it is a key point that ensures the fuze system of successfully recognizing target.
本文系统研究了利用特征基于模型SARA TR系统中,SAR图像目标特征提取方法和分类方法。
Methods of feature extraction and classification of target in model-based SAR ATR using feature are studied systemically in this paper.
在目标特征提取识别算法的基础上,还提出了阈值预测分割算法,并应用在序列图像的跟踪中,取得了较好效果。
Base on the recognition arithmetic, a segmentation method by forecasting threshold is proposed. Using this segmentation method in image tracking, satisfying effect is gotten.
本文主要研究PCNN在SAR降噪和目标特征提取过程中的应用,通过对比PCNN方法和现有方法的实验效果确定PCNN在SAR目标识别过程的适用性。
This paper research on SAR de-noises and target recognition with PCNN. Results were reached in this paper about adoption of PCNN in the de-noise and recognition of SAR image through tests.
结果表明,这种特征提取方法能有效地提取灰度图像目标纹理特征,并且对噪音和形状的变化具有强鲁棒性。
The results indicate this method can effectively extract texture feature of gray image target, and has robust to noise and change of target shape.
特征提取直接关系到雷达的目标识别性能。
Feature extraction for radar high range resolution profiles (HRRP) recognition is concerned.
该文详细讨论了基于HRRP的雷达自动目标识别的关键技术及研究现状,包括雷达hrrp的特性、预处理方法、特征提取方法及分类器设计方法等。
In this paper, we review the present research status and some key techniques in this field, including the property of HRRP, preprocessing methods, feature extraction and classifier design.
以毫米波敏感器在军事中的应用为背景,对毫米波敏感器信号的波形特征进行分析,采用小波变换进行目标信息的特征提取。
On the basis of the applications of MMW sensors to the munitions, this thesis analyses the wave characters of MMW sensors 'signal, use wavelet transform to extract the features of target information.
目标噪声特征提取是被动声纳目标识别系统的关键技术。
Feature extraction of targets radiated-noise is the key technique of passive sonar target recognition system.
本文研究了基于RCS序列的空间目标运动姿态判决、特征提取以及分类识别方法。
Moving statues adjudgement, character extraction and target classify methods of space targets based on RCS sequences are discussed in this paper.
研究了一种基于非相参雷达目标回波的特征提取算法。
The method of radar target waveform feature extraction is studied based on non coherent radar target echo.
特征提取是目标分类和识别的基础。
Feature extraction builds up the basis of target classification and recognition.
彩色形态变换作为一种数学形态学方法在彩色空间的延拓,可有效地应用于图象处理、图象编码和目标形状特征提取等。
As an extension of mathematical morphology to color space, the proposed transformation can be efficiently used in color image processing, image encoding and shape features extraction of objects, etc.
目标识别技术属于模式识别理论的研究范围,其关键在于特征提取和分类器的设计。
The target identification technology belongs to the research scope of the pattern recognition, its key lies in the characteristic withdraw and the sorter design.
本文采用的技术包括:皮肤检测、人脸检测、目标区域分割、敏感图像特征提取、分类器设计及过滤器在浏览器上的实现等。
Some key techniques are included, such as skin detection, face detection, object area segmentation, image features extraction, the design of classifier and the implement of filter based on browser.
步态轮廓的有效分割对于特征提取、目标分类等后期处理有非常重要的影响。
The segmentations of gait silhouettes have very important influence on feature extraction and subject classification.
它的研究主要由三部分构成:运动目标检测、特征提取和步态识别。
A gait recognition system consists of three primary parts: moving target detection, feature extraction and gait recognition.
提出了基于小波包变换和改进奇异值分解的高分辨雷达目标一维距离像特征提取方法。
A feature extraction method of high-range-resolution radar profiles, which takes advantage of wavelet packet transform and modified SVD (singular value decomposition) was proposed.
讨论了基于高分辨距离像(hrrp)的目标长度特征提取原理。
The basic theory of extraction of target projection length using high resolution range profile (HRRP) is discussed.
该系统的处理过程主要包括四个阶段:前景分割、目标检测、特征提取和车型分类。
The process of this system includes four phases: the prospects for segmentation, target detection, feature extraction and classification models.
目标噪声特征提取和目标分类器设计是被动声呐目标识别系统的关键技术。
Feature extraction of targets radiated noise and design of targets classifier are key technique of passive sonar target recognition system.
特征提取是水声目标分类的关键环节之一,用以获取各类目标的一些可鉴别性特征。
Feature extraction is one of key steps in underwater target classification system, to obtain some discriminatory information of various kinds of underwater targets.
特征提取是水声目标分类的关键环节之一,用以获取各类目标的一些可鉴别性特征。
Feature extraction is one of key steps in underwater target classification system, to obtain some discriminatory information of various kinds of underwater targets.
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