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In this paper we explore semantic segmentation of man-made scenes using fully connected conditional random field (CRF). Images of man-made scenes display strong contextual dependencies in the spatial ...
The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and sm...
Driven by the miniaturization, lightweight of positioning and remote sensing sensors as well as the urgent needs for fusing indoor and outdoor maps for next generation navigation, 3D indoor mapping fr...
Geographical Information System and Remote Sensing are tools which integrated can perform different environmental analysis. The Netherlands ITC (Institute for Aerospace Survey and Earth Sciences) deve...
Operational large-scale inventories, such as the State of Mississippi’s inventory system, must have algorithms to rapidly categorize the forest resource into statistically efficient strata. These proc...
Automated road tracking is important for map revision but is currently not reliable enough to be useful for industrial applications.Consequently semi-automatic road tracking has become the preferred s...
The differential morphological profile (DMP) can be used for automated extraction of multi-scale urban features, such as buildings, shadows, roads, and other man-made objects. However, characterizatio...
Recently, interests in 3D indoor modeling and positioning have been growing. Data fusion by using different sensors data is one of the 3D model producing methods. For a data fusion between two kinds o...
3D city modelling from airborne imagery includes mainly two parts: (1) image processing procedures and (2) 3D modelling for manmade objects such as buildings, roads and other objects. Line extraction ...
In order to perform object modelling by using images processing procedures, line or feature extraction and stereo matching will be performed in general. However, there are some issues of efficient 3D ...
In the last decade, the remote sensing community has observed a significant growth in number of satellites, sensors and their resolutions, thereby increasing the volume of data to be processed each da...
The world is increasingly depending on remotely sensed data. The data is regularly used for monitoring the earth resources and also for solving problems of the world like disasters, climate degradatio...
The study aimed at developing improved methods based on remote sensing and GIS techniques to increase cultivated area under irrigation. Landuse / landcover mapping was considered as the key component ...
Evolutionary computation, in the form of genetic programming, is used to aid information extraction process from high-resolution satellite imagery in a semi-automatic fashion. Distributing and paralle...
K-means is definitely the most frequently used partitional clustering algorithm in the remote sensing community. Unfortunately due to its gradient decent nature, this algorithm is highly sensitive to ...

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