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This paper presents a kernel-based approach for the change detection of remote sensing images. It detects change by comparing the probability density (PD), expressed as kernel functions, of the featur...
A kernel-based method for very high spatial resolution remote sensing image classification is proposed in this article. The new kernel method is based on spectral-spatial information and structure inf...
In this study estimation of tree damage from a windthrow event using feature detection on RGB high resolution imagery is assessed. An accurate quantitative assessment of the damage in terms of volume ...
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...
With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and ...
This paper extends kernel weighted GMM estimators recently proposed by the author in the context of homoskedastic processes to a class of models with conditionally heteroskedastic innovations. GMM e...
This paper proposes a distance-based kernel change detection algorithm (DKCD). The input vectors from two images of different times are mapped into a potentially much higher dimensional feature space...
Support Vector Machines (SVMs) are a statistical learning theory based techniques and have been applied to different fields. For the pattern recognition case, SVMs have been used for isolated handwri...
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance of KFDA depends on t...
Agriculture holds a pivotal role in context to India, which is basically agrarian economy. Crop type identification is a key issue for monitoring agriculture and is the basis for crop acreage and yiel...
In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imagerie...
Some engineering properties of mahogany seed and kernel were investigated and expressed as a function of moisture content. In the moisture ranges of 7.1–32% and 5.3–22% (d.b.), respectively, the seed ...
Supercritical fluid carbon dioxide (SC-CO2) at pressure 19.8 MPa and temperature 51°C with different amount of ethanol (0-100 mL) was studied the extraction of palm kernel oil from palm kernel cake. T...
The influence of three traditional unit operations (fruit storage, par-boiling duration and nut drying method) in the primary processing of the shea fruit in Ghana for the marketable kernel was assess...
A framework for multitemporal change detection based on kernel-composition is applied to a multispectral-multitemporal classification scenario, evaluated and compared to traditional change detection a...

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