LEADER 01152nam0 22002771i 450 001 UON00386493 005 20231205104552.706 010 $a978-03-00-13683-8 100 $a20101202d2009 |0itac50 ba 101 $aeng 102 $aUS 105 $a|||| ||||| 200 1 $aˆThe ‰familiarity of strangers$ethe Sephardic diaspora, Livorno, and cross-cultural trade in the early modern period$fFrancesca Trivellato 210 $aNew Haven$aLondon$cYale University Press$d2009 215 $aXIII, 470 p.$d 24 cm. 606 $aItalia$xLivorno$xStoria economica e sociale$xSec. 18.$3UONC077013$2FI 620 $aUS$dNew Haven$3UONL000121 620 $aGB$dLondon$3UONL003044 700 1$aTrivellato$bFrancesca$3UONV199369$0518899 712 $aYale University Press$3UONV246253$4650 801 $aIT$bSOL$c20250808$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00386493 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI EUR C A 0885 $eSI SC 46831 5 0885 $sBuono 996 $aFamiliarity of strangers$9839416 997 $aUNIOR LEADER 04192nam 22007215 450 001 9910574060903321 005 20251113191841.0 010 $a981-19-2746-4 024 7 $a10.1007/978-981-19-2746-1 035 $a(MiAaPQ)EBC7001367 035 $a(Au-PeEL)EBL7001367 035 $a(CKB)22898392200041 035 $a(PPN)269148302 035 $a(OCoLC)1322837872 035 $a(DE-He213)978-981-19-2746-1 035 $a(EXLCZ)9922898392200041 100 $a20220527d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning in Solar Astronomy /$fby Long Xu, Yihua Yan, Xin Huang 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (103 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$aPrint version: Xu, Long Deep Learning in Solar Astronomy Singapore : Springer,c2022 9789811927454 320 $aIncludes bibliographical references and index. 327 $aChapter 1: Introduction -- Chapter 2: Classical deep learning models -- Chapter 3: Deep learning in solar image classification tasks -- Chapter 4: Deep learning in solar object detection tasks -- Chapter 5: Deep learning in solar image generation tasks -- Chapter 6: Deep learning in solar forecasting tasks. 330 $aThe volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification, object detection and recognition. Astronomical study starts with imaging from recorded raw data, followed by image processing, such as image reconstruction, inpainting and generation, to enhance imaging quality. We study deep learning for solar image processing. First, image deconvolution is investigated for synthesis aperture imaging. Second, image inpainting is explored to repair over-saturated solar image due to light intensity beyond threshold of optical lens. Third, image translation among UV/EUV observation of the chromosphere/corona, Ha observation of the chromosphere and magnetogram of the photosphere is realized by using GAN, exhibiting powerful image domain transfer ability among multiple wavebands and different observation devices. It can compensate the lack of observation time or waveband. In addition, time series model, e.g., LSTM, is exploited to forecast solar burst and solar activity indices. This book presents a comprehensive overview of the deep learning applications in solar astronomy. It is suitable for the students and young researchers who are major in astronomy and computer science, especially interdisciplinary research of them. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aAstronomy 606 $aAstronomy$vObservations 606 $aMachine learning 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aAstronomy, Cosmology and Space Sciences 606 $aAstronomy, Observations and Techniques 606 $aMachine Learning 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aComputer Vision 615 0$aAstronomy. 615 0$aAstronomy 615 0$aMachine learning. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 14$aAstronomy, Cosmology and Space Sciences. 615 24$aAstronomy, Observations and Techniques. 615 24$aMachine Learning. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aComputer Vision. 676 $a523.70285631 700 $aXu$b Long$0720841 702 $aYan$b Yihua 702 $aHuang$b Xin 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910574060903321 996 $aDeep Learning in Solar Astronomy$92860233 997 $aUNINA