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Target identification from high resolution remote sensing image is a common task for many applications. In order to improve the performance of target identification, multiple classifier combination is...
With a lot of successful applications of neural network-based classification, it has been recognized the classification can produce more accurate results than conventional approaches for remotely-sens...
This paper examines the applicability of binary decision tree (DT) classifier and ASTER data for the monitoring of wetland vegetation at plant family level (eight dominant plant families in the study ...
In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong...
It is found that sub-pixel classifiers for classification of multi-spectral remote sensing data yield a higher accuracy. With this objective, a study has been carried out, where fuzzy set theory base...
Applying the region growing to the Kohonen’s self-organizing feature map, a non-supervised classifier for remotely sensed imagery data is proposed. If the self-organizing feature map is made large e...
This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR) and opti...
Research of automatic vehicle detection in aerial images has been done with a lot of innovation and constantly rising success for years. However information was mostly taken from a single image only. ...
Evaluation of fuzzy based classifier to identify and map a specific crop using multi-spectral and time series data spanning over one growing season. The temporal data is pre-processed with respect to ...

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