针对国产高分一号卫星(GF-1)成像质量是否可以满足区域生态环境监测需求的问题,开展了宽幅多光谱相机(wide field view,WFV)在荒漠绿洲过渡带的成像质量评估研究。从辐射质量、纹理、地类识别精度和归一化植被指数等方面构建评估指标,...针对国产高分一号卫星(GF-1)成像质量是否可以满足区域生态环境监测需求的问题,开展了宽幅多光谱相机(wide field view,WFV)在荒漠绿洲过渡带的成像质量评估研究。从辐射质量、纹理、地类识别精度和归一化植被指数等方面构建评估指标,定量分析了GF-1 WFV和Landsat-8OLI在荒漠绿洲过渡带的成像质量差异。结果表明:GF-1 WFV影像虽然具有较高的空间分辨率,但在辐射质量、地类识别效果、纹理信息及植被指数等方面与Landsat-8OLI相比有一定差距;GF-1 WFV影像的信噪比优势明显,对噪声的抑制效果较好;通过与纹理信息的波段组合,可以有效提高GF-1WFV影像的地物识别效果,缩小与Landsat-8OLI在分类精度上的差距;鉴于明显的光谱范围差异,二者归一化植被指数数据在协同应用的过程中宜分地物类型转换,在西北荒漠绿洲过渡带的国土资源调查、城市规划、农情监测等方面可发挥积极作用。展开更多
With the rapid growth of web-based social networking technologies in recent years, author identification and analysis have proven increasingly useful. Authorship analysis provides information about a document’s autho...With the rapid growth of web-based social networking technologies in recent years, author identification and analysis have proven increasingly useful. Authorship analysis provides information about a document’s author, often including the author’s gender. Men and women are known to write in distinctly different ways, and these differences can be successfully used to make a gender prediction. Making use of these distinctions between male and female authors, this study demonstrates the use of a simple stream-based neural network to automatically discriminate gender on manually labeled tweets from the Twitter social network. This neural network, the Modified Balanced Winnow, was employed in two ways;the effectiveness of data stream mining was initially examined with an extensive list of n-gram features. Feature selection techniques were then evaluated by drastically reducing the feature list using WEKA’s attribute selection algorithms. This study demonstrates the effectiveness of the stream mining approach, achieving an accuracy of 82.48%, a 20.81% increase above the baseline prediction. Using feature selection methods improved the results by an additional 16.03%, to an accuracy of 98.51%.展开更多
针对海量经济数据无法正确识别并进行实时分析、存储的缺陷,提出了一种基于机器学习的数字识别方法。首先通过相机实时采集LED屏幕数据,采用人工设置ROI(Region of Image,感兴趣区域)的方式划分识别区域,然后采用水平投影法定位数字区...针对海量经济数据无法正确识别并进行实时分析、存储的缺陷,提出了一种基于机器学习的数字识别方法。首先通过相机实时采集LED屏幕数据,采用人工设置ROI(Region of Image,感兴趣区域)的方式划分识别区域,然后采用水平投影法定位数字区域与分割单个目标,再提取归一化后识别目标的投影特征分布,并在训练阶段将其作为学习模型SVM(Support Vector Machine,支持向量机)的输入,最后用完成的SVM模型作为经济数据识别方法的分类器,并将识别数据导入后台数据库进行后续分析。实验表明:以某一股票软件为例,该系统可以准确快速识别屏幕上的经济数据,较传统方式效率更高,速度更快。展开更多
文摘With the rapid growth of web-based social networking technologies in recent years, author identification and analysis have proven increasingly useful. Authorship analysis provides information about a document’s author, often including the author’s gender. Men and women are known to write in distinctly different ways, and these differences can be successfully used to make a gender prediction. Making use of these distinctions between male and female authors, this study demonstrates the use of a simple stream-based neural network to automatically discriminate gender on manually labeled tweets from the Twitter social network. This neural network, the Modified Balanced Winnow, was employed in two ways;the effectiveness of data stream mining was initially examined with an extensive list of n-gram features. Feature selection techniques were then evaluated by drastically reducing the feature list using WEKA’s attribute selection algorithms. This study demonstrates the effectiveness of the stream mining approach, achieving an accuracy of 82.48%, a 20.81% increase above the baseline prediction. Using feature selection methods improved the results by an additional 16.03%, to an accuracy of 98.51%.
文摘针对海量经济数据无法正确识别并进行实时分析、存储的缺陷,提出了一种基于机器学习的数字识别方法。首先通过相机实时采集LED屏幕数据,采用人工设置ROI(Region of Image,感兴趣区域)的方式划分识别区域,然后采用水平投影法定位数字区域与分割单个目标,再提取归一化后识别目标的投影特征分布,并在训练阶段将其作为学习模型SVM(Support Vector Machine,支持向量机)的输入,最后用完成的SVM模型作为经济数据识别方法的分类器,并将识别数据导入后台数据库进行后续分析。实验表明:以某一股票软件为例,该系统可以准确快速识别屏幕上的经济数据,较传统方式效率更高,速度更快。
