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Titlebook: Digital Multimedia Communications; 19th International F Guangtao Zhai,Jun Zhou,Jia Wang Conference proceedings 2023 The Editor(s) (if appli

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發(fā)表于 2025-3-21 19:36:56 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Digital Multimedia Communications
副標(biāo)題19th International F
編輯Guangtao Zhai,Jun Zhou,Jia Wang
視頻videohttp://file.papertrans.cn/280/279570/279570.mp4
叢書(shū)名稱(chēng)Communications in Computer and Information Science
圖書(shū)封面Titlebook: Digital Multimedia Communications; 19th International F Guangtao Zhai,Jun Zhou,Jia Wang Conference proceedings 2023 The Editor(s) (if appli
描述??.This book constitutes the refereed proceedings of the? 19th International Forum on Digital Multimedia Communication, IFTC 2022, held in Shanghai, China, December 8–9, 2022..The 40 full papers included in this book were carefully reviewed and selected from 112 submissions. They were organized in topical sections as follows: Computer Vision; Image Analysis; Quality Assessment; Video Processing; Machine Learning; and Big data..
出版日期Conference proceedings 2023
關(guān)鍵詞computer vision; artificial intelligence; image segmentation; pattern recognition; image coding; database
版次1
doihttps://doi.org/10.1007/978-981-99-0856-1
isbn_softcover978-981-99-0855-4
isbn_ebook978-981-99-0856-1Series 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 Singapor
The information of publication is updating

書(shū)目名稱(chēng)Digital Multimedia Communications影響因子(影響力)




書(shū)目名稱(chēng)Digital Multimedia Communications影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Digital Multimedia Communications網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Digital Multimedia Communications網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Digital Multimedia Communications被引頻次




書(shū)目名稱(chēng)Digital Multimedia Communications被引頻次學(xué)科排名




書(shū)目名稱(chēng)Digital Multimedia Communications年度引用




書(shū)目名稱(chēng)Digital Multimedia Communications年度引用學(xué)科排名




書(shū)目名稱(chēng)Digital Multimedia Communications讀者反饋




書(shū)目名稱(chēng)Digital Multimedia Communications讀者反饋學(xué)科排名




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發(fā)表于 2025-3-21 21:05:39 | 只看該作者
1865-0929 nized in topical sections as follows: Computer Vision; Image Analysis; Quality Assessment; Video Processing; Machine Learning; and Big data..978-981-99-0855-4978-981-99-0856-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
板凳
發(fā)表于 2025-3-22 03:48:22 | 只看該作者
地板
發(fā)表于 2025-3-22 06:43:57 | 只看該作者
Parameters, Scales and Geostrophic Balance and the CNN structure can provide additional local information to the transformer. The fusion of global information and local information is conducive to the second transfer encoder to make better decisions. Experiments results on large-size dataset for industrial smoke detection illustrate the effectiveness of the proposed model.
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發(fā)表于 2025-3-22 15:48:55 | 只看該作者
John Vince MTech, PhD, DSc, CEng, FBCSmage. Then we design a novel Kernel Fast Fourier Convolution (KFFC) to filter the image feature of the transitional image with the raw blur kernel in the frequency domain. Extensive experiments show that our methods achieve favorable and robust results.
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發(fā)表于 2025-3-22 20:41:00 | 只看該作者
Errata,hts of features at different scales. We conduct extensive experiments on Hubei water dataset we constructed, The results show the framework effectively improves the accuracy of water segmentation and greatly improves the visual effect of segmentation, which is 5.9% higher in self-made dataset with advanced methods.
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發(fā)表于 2025-3-23 00:16:16 | 只看該作者
Pedestrian Re-recognition Based on?Memory Network and?Graph Structuresults shows that the Rank 1 of the GCPRN network on iLIDS Video re-identification (iLIDS-VID) dataset reaches . and Rank 5 reached ., surpassing the Unsupervised Tracklet Association Learning (UTAL) and Temporal Knowledge Propagation (TKP) algorithm that reached a high level on the iLIDS-VID dataset.
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發(fā)表于 2025-3-23 04:15:57 | 只看該作者
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發(fā)表于 2025-3-23 07:53:28 | 只看該作者
Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Imageet. The proposed method can implement the high-efficiency encoding of X-ray images, and then swiftly transmit the telemedicine-oriented chest images. The experimental results show that compared with the state-of-the-art predictive coding methods, both rate-distortion and complexity performance of our FAPC method have enough competitive advantages.
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