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Titlebook: Computer Vision and Image Processing; 8th International Co Harkeerat Kaur,Vinit Jakhetiya,Sanjeev Kumar Conference proceedings 2024 The Edi

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發(fā)表于 2025-3-21 16:35:07 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Computer Vision and Image Processing
副標(biāo)題8th International Co
編輯Harkeerat Kaur,Vinit Jakhetiya,Sanjeev Kumar
視頻videohttp://file.papertrans.cn/243/242298/242298.mp4
叢書(shū)名稱(chēng)Communications in Computer and Information Science
圖書(shū)封面Titlebook: Computer Vision and Image Processing; 8th International Co Harkeerat Kaur,Vinit Jakhetiya,Sanjeev Kumar Conference proceedings 2024 The Edi
描述.The three-volume set CCIS 2009, 2010 and 2011 constitutes the refereed post-conference proceedings of the 8th International Conference on Computer Vision and Image Processing, CVIP 2023, held in Jammu, India, during November 3–5, 2023.?..?..The 140 revised full papers presented in these proceedings were carefully reviewed and selected from?461?submissions.?The papers focus on?various important and emerging topics in image processing, computer vision applications, deep learning, and machine learning techniques in the domain..
出版日期Conference proceedings 2024
關(guān)鍵詞artificial intelligence; color image processing; color images; computer systems; computer vision; image a
版次1
doihttps://doi.org/10.1007/978-3-031-58181-6
isbn_softcover978-3-031-58180-9
isbn_ebook978-3-031-58181-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書(shū)目名稱(chēng)Computer Vision and Image Processing影響因子(影響力)




書(shū)目名稱(chēng)Computer Vision and Image Processing影響因子(影響力)學(xué)科排名




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書(shū)目名稱(chēng)Computer Vision and Image Processing被引頻次




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書(shū)目名稱(chēng)Computer Vision and Image Processing讀者反饋




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978-3-031-58180-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Brian Steele,John Chandler,Swarna Reddy by the selfie apps, face recognition becomes more challenging with existing approaches. We develop a challenging Wild Selfie Dataset (WSD) where the images are captured from the selfie cameras of different smart phones. The WSD dataset contains 45,424 images from 42 individuals (i.e., 24 female and
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Nearest Neighbor Queries over Encrypted Dataipulation of ECG signals can result in inaccurate diagnosis or treatment because these signals are crucial for identifying and monitoring cardiovascular illnesses. Also, these signals are frequently sent via the internet, raising the possibility of unwanted access and manipulation. Hence, ECG signal
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https://doi.org/10.1007/978-3-030-58896-0s provide better image understanding and interpretation of features. Because the number of NIR-RGB paired datasets is limited and often unavailable, a method to convert a given NIR image to an RGB image is highly desirable. The present work proposes an unsupervised image to image translation techniq
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Range Queries over Encrypted Datag cracks for distress analysis in challenging background scenarios is a difficult task as there is no clear boundary that separates cracks from the background. Some of the other perceptually noted challenges with the images are variations in color, intensity, depth, blur, motion-blur, orientation, r
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