思考才皱眉
发表于 2025-3-25 04:39:01
Introduction,tional neural network has been verified most efficient for processing image. To process time series input, like video, recurrent neural network, e.g., long short-term memory (LSTM), was developed, which was widely known for forecasting the future, e.g., event occurrence, physical parameter predictio
Hallowed
发表于 2025-3-25 09:56:37
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江湖郎中
发表于 2025-3-25 14:54:23
Deep Learning in Solar Astronomy978-981-19-2746-1Series ISSN 2191-5768 Series E-ISSN 2191-5776
浪荡子
发表于 2025-3-25 17:53:11
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Organization
发表于 2025-3-25 22:53:47
978-981-19-2745-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
失眠症
发表于 2025-3-26 02:35:35
https://doi.org/10.1007/978-3-662-37014-8 techniques. It has been particularly successful in computer vision, machine translation, speech recognition and natural language processing. Modern astronomy concerns a big data challenge owning to high-resolution, high-precision and high-cadence telescopes. The big data presents a great challenge
骚动
发表于 2025-3-26 04:47:11
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Habituate
发表于 2025-3-26 08:57:18
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PALL
发表于 2025-3-26 14:19:43
https://doi.org/10.1007/978-3-662-01274-1ellite continuously record high-resolution and high-cadence full-disk solar images. These images are used for solar activity forecasting and statistical analysis. Usually, it is required to mine key information from full-disk images firstly. Then, over extracted information, one can establish classi
抵押贷款
发表于 2025-3-26 19:46:12
https://doi.org/10.1007/978-3-642-53067-8ty of image generation which is more challenging than classification. In this chapter, several applications of deep learning in solar image enhancement, reconstruction and processing are presented, including image deconvolution of solar radioheliograph, desaturation of solar imaging, generating magn