1、

3D Model Feature Extraction Based on Convolutional Networks

基于卷积网络的三维模型特征提取

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2、

Feature Extraction and Recognition of Loudspeaker Response Signal Based on Principal Components Analysis

基于PCA的扬声器响应信号特征提取及识别

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3、

With the analyzing on the relationship between azimuth and SAR target distribution, another feature extraction method based on hyper-sphere projection space is proposed.

在分析方位角与SAR目标分布关系的基础上,提出了基于超球面投影空间的特征提取方法,通过超球面投影获得SAR样本的全方位分布特性,进而消除了方位角对SAR目标识别的影响。

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4、

A Method for Modulation Feature Extraction of Underwater Target Radiated Noise

一种水下目标辐射噪声调制特征提取方法

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5、

Study of Change Feature Extraction Algorithms in SAR Target Discrimination

SAR目标鉴别中的变化特征提取算法研究

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6、

Power Gathering-Point and Feature Extraction Method of Target Signal

信号能量聚点与特征提取方法研究

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7、

Target echo signal feature extraction and material recognition of ultra-wideband ground-penetrating radar

超宽带探地雷达目标回波信号特征提取与材质识别

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8、

Study on Feature Extraction and Text Representation Technology in Topic Tracking

面向话题追踪的特征选取与文本表示技术的研究

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9、

Feature extraction and text representation are keys to the performance of text classification.

特征提取及文本表示是影响文本分类结果的关键。

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10、

According to the characteristic of topic tracking task, we study the feature extraction and text representation technology in it.

本文根据话题追踪任务的特点,研究了面向话题追踪的特征选取和文本表示技术。

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11、

Research on Feature Extraction and Collection for Underwater Target Signal

水下目标信号特征提取与采集研究

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12、

Trends Visual Effects Based Feature Extraction for Dynamic Radar Target Echo Series

基于视觉效果的雷达目标动态回波序列特征提取方法

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13、

Iris recognition comprises some kernel processes as iris positioning, texture feature extraction, coding and recognition.

虹膜识别通常包含虹膜定位、特征提取以及编码和识别几个关键步骤。

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14、

Local Walsh transform belongs to the digital image processing family, and it has better texture discrimination performance compared with other texture feature extraction methods.

局部沃尔什变换属于数字图像处理方法的一种。与其他纹理特征提取方法相比,该方法提取的特征具有更好的纹理鉴别性能。

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15、

At the same time, analysis the existing method of text processing and text feature extraction on semantic similarity calculation.

同时,详细分析了已有的文本处理、文本特征提取以及语义相似度计算方法。

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16、

Image feature extraction mainly utilizes auto-extraction of low-level visual feature ( color, texture, profile, shape etc.) from image data, to deeply describe high-level semantic information.

提取图像特征主要利用从图像数据中自动抽取出底层特征,如颜色、纹理、轮廓和形状等特征,进而描述出高层语义信息。

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17、

Phase feature extraction and its application in texture segmentation

相位特征提取及在纹理分割中的应用

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18、

In segmentation an image is expressed as a number of non-overlapping connected regions which provide necessary information for feature extraction, object recognition and other high-level image understanding.

图像分割把一幅图像表示为若干不相重叠的连通区域,为特征提取、目标识别等高层的图像理解提供必要的信息。

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19、

This thesis studies target association problem in the non-overlapping surveillance cameras and makes an in-depth study on target feature extraction and matching.

本文主要研究非重叠监控摄像机中的目标关联,并针对目标关联中的特征提取与匹配进行了深入的研究。

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20、

An Improved Text Feature Extraction Algorithm Based on N-Gram

一种基于N-Gram改进的文本特征提取算法

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