A hierarchical object detection method based on vision saliency was proposed for automatic remote sensing image interpretation.
针对遥感图像自动判读的应用场景,提出了一种基于视觉显著性的分层目标检测方法。
The image-based approach may reduce computational delay, eliminate the necessity for image interpretation and eliminate errors due to sensor modeling and camera calibration.
该方法可以减少计算延时,并且对摄像机和机械臂的校准误差和目标模型误差具有较强的鲁棒性。
The Interpretation of Remote sensing image Indoor beforehand can greatly increase the production efficiency of Present land use map based on Remote sensing image.
利用遥感影像制作土地利用现状图时,在室内先对影像进行预判解译,可以提高土地利用现状图制作的工作效率。
A hierarchical object detection method based on vision saliency was proposed for automatic sensing image interpretation.
针对遥感图像自动判读的应用场景,提出了一种基于视觉显著性的分层目标检测方法。
Because traditional manual visual interpretation was time and labor consuming, it was necessary to extract the information based on remote sensing image.
传统的人工目视解译费时费力,基于遥感影像的居民地信息自动提取势在必行。
Because traditional manual visual interpretation was time and labor consuming, it was necessary to extract the information based on remote sensing image.
传统的人工目视解译费时费力,基于遥感影像的居民地信息自动提取势在必行。
应用推荐