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100   $a20230705d2023      uy             0
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aDeep Learning and Computer Vision in Remote Sensing /$fFahimeh Farahnakian, Jukka Heikkonen, Pouya Jafarzadeh, editors
210  1$aBasel :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2023.
215   $a1 online resource (572 pages)
311   $a3-0365-6368-7 
330   $aIn the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
606   $aRemote sensing
615  0$aRemote sensing.
676   $a621.3678
702   $aJafarzadeh$b Pouya
702   $aHeikkonen$b Jukka
702   $aFarahnakian$b Fahimeh
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910683389903321
996   $aDeep Learning and Computer Vision in Remote Sensing$93085006
997   $aUNINA