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In this paper, we present a kernel sparse subspace clustering with spatial max pooling operation (KSSC-SMP) algorithm for hyperspectral remote sensing imagery. Firstly, the feature points are mapped f...
For a clustering algorithm, the number of clusters is a key parameter since it is directly related to the number of homogenous regions in the given image. Although ISODATA clustering algorithm can det...
Ecological environment quality comprehensive evaluation evaluate different cells’ ecological environment quality, on the basis of region eco-environment investigation , the indexes and math methods se...
We implemented a strategy for terrain, vegetation and building detection, based on laser range data only. The result was obtained by working on raw data, so we were able to take advantage of the full ...
Rice Agriculture, mainly cultivated in South Asia regions, is being monitored for extracting crop parameter, crop area, crop growth profile, crop yield using both optical and microwave remote sensing....
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 ...
Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. Data clustering algorithms have been intensively used for ima...
Developing fully automatic systems is still an active research topic in 3D building model reconstruction. While a general solution to the building reconstruction problem relies on collecting and group...

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