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101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 00$aAdvanced Machine Learning and Deep Learning Approaches for Remote Sensing /$fedited by Gwanggil Jeon
210  1$a[Place of publication not identified] :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2023.
215   $a1 online resource (362 pages)
311   $a3-0365-7947-8 
330   $aThis reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.
606   $aDeep learning (Machine learning)
606   $aMachine learning
606   $aRemote sensing
615  0$aDeep learning (Machine learning)
615  0$aMachine learning.
615  0$aRemote sensing.
676   $a621.3678
702   $aJeon$b Gwanggil
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910734348503321
996   $aAdvanced Machine Learning and Deep Learning Approaches for Remote Sensing$93401559
997   $aUNINA