| 卷积神经网络GPS坐标转换方法 |
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| 引用本文： | 崔方,赵庶旭.卷积神经网络GPS坐标转换方法[J].测绘通报,2019,0(3):1-5. |
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| 作者姓名： | 崔方 赵庶旭 |
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| 作者单位： | 兰州交通大学电子与信息工程学院,甘肃 兰州,730070;兰州交通大学电子与信息工程学院,甘肃 兰州,730070 |
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| 基金项目： | 甘肃省科技支撑计划基金（1504GKCA018） |
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| 摘 要： | GPS坐标转换方法对于GPS空间定位系统至关重要。目前已有很多方法被提出用于转换GPS坐标,但效果并不是很显著。究其原因,是因为大多数都存在模型误差和投影误差。针对目前方法的不足,本文利用深度学习对非结构化数据处理的优势,提出了一种基于卷积神经网络(CNN)的GPS坐标转换方法。该方法将GPS数据转化为非结构化图片数据,以其作为CNN的输入层来训练GPS坐标转换模型,这样能够最小化满足对数据的预处理要求,无监督地从数据中学习出有效特征。试验结果表明,该方法与传统坐标转换方法相比,具有更高的转换精度。
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| 关 键 词： | 深度学习 神经网络 卷积神经网络 坐标转换 全球定位系统 |
| 收稿时间： | 2018-03-13 |
GPS coordinates transformation based on convolutional neural network |
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| CUI Fang,ZHAO Shuxu.GPS coordinates transformation based on convolutional neural network[J].Bulletin of Surveying and Mapping,2019,0(3):1-5. |
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| Authors: | CUI Fang ZHAO Shuxu |
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| Institution: | School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China |
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| Abstract: | The GPS coordinate conversion method is crucial for GPS space location system.In the past,many methods have been proposed to convert GPS coordinates,but the effect is not very significant.The reason is that most of the models have model errors and projection errors.In view of the shortcomings of the current methods,this paper proposes a GPS coordinate transformation based on convolution neural network (CNN) by using the advantages of deep learning on unstructured data processing method.This method transforms GPS data into unstructured image data and uses these unstructured image data as the input layer of CNN to train the GPS coordinate transformation model so as to minimize the requirement of data preprocessing and to learn from the data without supervision out of effective features.Experimental results show that this method has higher conversion accuracy than the traditional coordinate transformation method. |
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| Keywords: | deep learning neural networks convolutional neural networks coordinate transformation GPS |
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