搜索资源列表
fetaure_extraction_lidar
- With the rapid development of remote sensing technology, three dimensional coordinates and intensity information of observation target can be obtained directly from LIDAR system. It is one of the important issues in the study on LIDAR data process
cloudModels
- 有关数据挖掘的云模型的一些应用论文，很有参考价值的-Data mining on some applications of the cloud model papers worthy ~ ~
LIDAR-Data-Classification
- 用K领域实现点云分类，国外算法，希望对你有用！-Achieved with the K point cloud field classification algorithm abroad, I hope useful to you!
LidarSeq
- 点云分割的函数文件，适合于lidar点云数据，具有很强大的点云处理功能-Point cloud segmentation function file, suitable for lidar point cloud data, with a very powerful point cloud processing
angle.lidar
- 【无人驾驶传感器之64线激光雷达】 velodyne hdl64es2 64线激光雷达点云数据处理之雷达扫描范围图-[64 line laser radar sensor of the unmanned] velodyne hdl64es2 64 lines LIDAR point cloud data processing of the scan range radar chart
feature.dr
- 【无人驾驶传感器之64线激光雷达】 velodyne hdl64es2 64线激光雷达点云数据处理之雷达返回值与转角关系-[64 line laser radar sensor of the unmanned] velodyne hdl64es2 64 lines lidar point cloud radar data processing of the return value and the angular relationship
filter.dr
- 【无人驾驶传感器之64线激光雷达】 velodyne hdl64es2 64线激光雷达点云数据处理之角分割与滤波方法-[64 line laser radar sensor of the unmanned] angle velodyne hdl64es2 64 lines LIDAR point cloud data processing method of segmentation and filtering
一种基于MapReduce的粗糙集并行属性约简算法
- 云计算技术是海量数据挖掘的一种高效解决方案，将MapＲeduce 并行计算模型与粗糙集属性约简算法相结合，提出一种基于MapＲeduce 的浓缩布尔矩阵并行属性约简算法。该算法提高了粗糙集属性约简算法对大数据的处理能力和效率，并能适应云计算环境。实验结果表明，所提算法具有良好的效率、加速比和可扩展性。(Cloud computing technology is a high efficient solution for massive data mining.)