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The results of the study show the use of GPUs significantly increased speed when compared to a traditional Central Processing Unit based classification setup.
The results of the study show the use of GPUs significantly increased speed when compared to a traditional Central. Processing Unit based classification setup.
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Paper Detail ; Title: TEXTURE CLASSIFICATION OF VERY HIGH RESOLUTION UAS IMAGERY USING A GRAPHICS PROCESSING UNIT ; Authors: Sathishkumar Samiappan; Mississippi ...
Riparian Zones Classification Using Satellite/UAV Synergy ... Texture Classification of Very High Resolution UAS Imagery Using a Graphics Processing Unit.
Jun 26, 2018 · A convolutional neural network (CNN) was developed to classify aerial photographs into seven land cover classes such as building, grassland, dense vegetation, ...
... The output image generated by texture analysis is often classified directly or supplemented to the original data in classification [Hsu, 1978; Marceau et.
This study demonstrated that image textures can assist wheat monitoring to achieve higher estimation accuracy of LAI and LDM.
Missing: Graphics Unit.
Results demonstrate the ability of UAS technology to collect hyperspatial, multispectral aerial images in a coastal wetland, and to produce very-high-resolution ...
This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to ...
Missing: UAS | Show results with:UAS
In this paper, we explore the potentialities of using wavelet-based multivariate models for the classification of very high resolution optical images.