机译:结合迭代训练样本选择和马尔可夫随机场模型的自动土地覆盖更新方法
State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;
State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China,Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA;
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
机译:利用迭代训练样本选择和马尔可夫随机场模型将多时相遥感数据应用于自动土地覆盖更新
机译:基于马尔可夫随机场模型的高程自动选择与区域合并流域分割
机译:高斯马尔可夫随机字段快速更新的采样策略
机译:马可夫随机场模型中用于信息检索的自动特征选择
机译:使用地统计学和多尺度马尔可夫随机场将数据集成到高分辨率油藏模型中。
机译:基于隐马尔可夫随机场模型和期望最大化的电子显微图像中颗粒自动识别的图像分割
机译:信息检索的马尔可夫随机场模型中的自动特征选择