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Titlebook: Intelligent Computing and Block Chain; First BenchCouncil I Wanling Gao,Kai Hwang,Zhifei Zhang Conference proceedings 2021 Springer Nature

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發(fā)表于 2025-3-21 18:55:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Computing and Block Chain
副標(biāo)題First BenchCouncil I
編輯Wanling Gao,Kai Hwang,Zhifei Zhang
視頻videohttp://file.papertrans.cn/470/469499/469499.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Intelligent Computing and Block Chain; First BenchCouncil I Wanling Gao,Kai Hwang,Zhifei Zhang Conference proceedings 2021 Springer Nature
描述This book constitutes the refereed post-conference proceedings of the Second BenchCouncil International Federated Intelligent Computing and Block Chain Conferences, FICC 2020, held in Qingdao, China, in October/ November 2020..The 32 full papers and 6 short papers presented were carefully reviewed and selected from 103 submissions. The papers of this volume are organized in topical sections on AI and medical technology; AI and big data; AI and block chain; AI and education technology; and AI and financial technology..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; blockchain; computer systems; computer vision; data mining; database; federated i
版次1
doihttps://doi.org/10.1007/978-981-16-1160-5
isbn_softcover978-981-16-1159-9
isbn_ebook978-981-16-1160-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2021
The information of publication is updating

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Intelligent Computing and Block Chain978-981-16-1160-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Li Lin,Jiewei Wu,Pujin Cheng,Kai Wang,Xiaoying Tang
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Jiewei Wu,Yue Zhang,Weikai Huang,Li Lin,Kai Wang,Xiaoying Tang
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BLU-GAN: Bi-directional ConvLSTM U-Net with Generative Adversarial Training for Retinal Vessel Segmere maps extracted from encoding path layers and the previous decoding up-convolutional layers and to replace the simple skip-connection used in the original U-Net. Moreover, we use densely connected convolutions in certain layers to strengthen feature propagation, encourage feature reuse, and substa
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