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- W3217757659 abstract "Nowadays hyperspectral image processing is gaining much interest of researchers due to the fact that hyperspectral images offer high spectral resolution and also due to its various applications in different fields. The growing interest in hyperspectral imaging has given rise to many innovative and novel techniques. These techniques are used for segmentation, detection, feature extraction, and classification of hyperspectral images using optimal resources and also taking into consideration various other factors such as time complexity and accuracy of results. Researchers have proposed some new techniques and yet other researchers are working on hybridization of earlier techniques to improve the accuracy and to get much better results. In this paper, a study about some of the hyperspectral segmentation techniques has been given along with a review about the recent approaches of segmentation techniques that have been proposed by some of the researchers. The proposed techniques have been briefly discussed and the datasets used by the researchers along with their results have been given in the tabulated form. The outcomes obtained while comparing their proposed techniques with some other techniques and also the shortcomings of the methods faced by the authors have also been made available in a tabulated form." @default.
- W3217757659 created "2021-12-06" @default.
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- W3217757659 date "2021-11-28" @default.
- W3217757659 modified "2023-09-23" @default.
- W3217757659 title "A Fundamental Review on Hyperspectral Segmentation Algorithms" @default.
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- W3217757659 doi "https://doi.org/10.1007/978-981-16-7305-4_17" @default.
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