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Hyperspectral sensor generates huge datasets which conveys abundance of information. However, it poses many challenges in the analysis and interpretation of these data. Deep networks like VGG16, VGG19 are difficult to directly apply for hyperspectral image (HSI) classification because of its higher number of layers which in turn requires high level of system resources. This article suggests a novel...
The recent advancement in remote sensing has made it possible to capture hyper spectral images with more than hundred bands which include spectrum beyond the visible range as well. This increased number of spectral dimension gives detailed information about the objects and hence increases the classification accuracy. But at the same time it also increases the computational complexity. So, reducing...
In this paper we have discussed the recognition of Meetei Mayek script with a Support Vector machine classifier. Distance profile feature and background directional distribution features are used as the feature vectors for training the SVM classifier. A comparative study is made on the performance between profile feature and background directional feature efficiency using SVM. Then a hybrid feature...
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