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Titlebook: Indigenous Innovation Pathways with Chinese Characteristics; Qingrui Xu,Jin Chen Book 2023 Zhejiang University Press 2023 Innovation in ma

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發(fā)表于 2025-3-21 20:00:08 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Indigenous Innovation Pathways with Chinese Characteristics
編輯Qingrui Xu,Jin Chen
視頻videohttp://file.papertrans.cn/464/463631/463631.mp4
概述Presents an overview of China’s innovation development.Reveals the innovation-driven economic growth of Chinese enterprises in the global context.Is the first book to deeply analyze the road of China’
叢書名稱Qizhen Humanities and Social Sciences Library
圖書封面Titlebook: Indigenous Innovation Pathways with Chinese Characteristics;  Qingrui Xu,Jin Chen Book 2023 Zhejiang University Press 2023 Innovation in ma
描述.This book aims to answer the key question facing China in building an innovative country: What kind of indigenous innovation path with Chinese characteristics should be taken? This book conducts an in-depth analysis of the indigenous innovation path with Chinese characteristics from two dimensions: path evolution and level (enterprise, industry, region, and country). It puts forward the leading path of innovation with Chinese characteristics and also offers policy suggestions. .
出版日期Book 2023
關(guān)鍵詞Innovation in management; Innovation in technology; China’s path; Innovation in business; Sustainable de
版次1
doihttps://doi.org/10.1007/978-981-99-5199-4
isbn_softcover978-981-99-5201-4
isbn_ebook978-981-99-5199-4Series ISSN 2731-5304 Series E-ISSN 2731-5312
issn_series 2731-5304
copyrightZhejiang University Press 2023
The information of publication is updating

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發(fā)表于 2025-3-21 22:27:59 | 只看該作者
ysis, pattern recognition, image enhancement of spine imaging, image-guided spine intervention and treatment, multimodal image registration and fusion for spine imaging, novel visualization techniques, segmentation techniques for spine imaging, statistical and geometric modeling for spine and verteb
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發(fā)表于 2025-3-22 02:56:52 | 只看該作者
Qingrui Xu,Jin Chen harness the complementary information from different modalities, we propose a modality dropout strategy to alleviate the co-adaption issue during the training. We evaluated our method on the .. Our method achieved the best overall performance with the mean segmentation Dice as 91.2% and localizatio
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發(fā)表于 2025-3-22 11:29:21 | 只看該作者
Qingrui Xu,Jin Chen quality, and translation of the vertebrae within the image, especially compared to when no augmentations were used (DSC?=?0.774?±?0.188). Integration of this method into a clinical tool will allow accurate and robust quantitative assessment of mechanical stability, aiding clinical decision making t
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發(fā)表于 2025-3-22 13:17:33 | 只看該作者
into account the entire image. The functionality of the RC component is differentiable. Thus, it can be merged to the deep neural network, and trained end-to-end with other sub-networks. We achieve identification rates of 85.32% and 52.28% for sagittal and coronal views and localization distance of
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發(fā)表于 2025-3-22 17:27:16 | 只看該作者
Qingrui Xu,Jin Chen into account the entire image. The functionality of the RC component is differentiable. Thus, it can be merged to the deep neural network, and trained end-to-end with other sub-networks. We achieve identification rates of 85.32% and 52.28% for sagittal and coronal views and localization distance of
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發(fā)表于 2025-3-23 07:38:42 | 只看該作者
Qingrui Xu,Jin Chenposes. Registration accuracy was assessed using bone-implanted mini screws. The average fiducial registration error and target registration error (TRE) for ground-truth probe registration was . and ., respectively. The accuracy for iSV registration was . in TRE and was . for surface reconstruction.
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