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Titlebook: Image and Graphics; 10th International C Yao Zhao,Nick Barnes,Chunyu Lin Conference proceedings 2019 Springer Nature Switzerland AG 2019 ar

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發(fā)表于 2025-3-21 17:03:45 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Image and Graphics
副標題10th International C
編輯Yao Zhao,Nick Barnes,Chunyu Lin
視頻videohttp://file.papertrans.cn/462/461481/461481.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Image and Graphics; 10th International C Yao Zhao,Nick Barnes,Chunyu Lin Conference proceedings 2019 Springer Nature Switzerland AG 2019 ar
描述.This three-volume set LNCS 11901, 11902, and 11903 constitutes the refereed conference proceedings of the 10tht.h. International Conference on Image and Graphics, ICIG 2019, held in Beijing, China, in August 2019. The 183 full papers presented were selected from 384 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking..
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; compression algorithms; computer vision; game and animation; image coding; image
版次1
doihttps://doi.org/10.1007/978-3-030-34113-8
isbn_softcover978-3-030-34112-1
isbn_ebook978-3-030-34113-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

書目名稱Image and Graphics影響因子(影響力)




書目名稱Image and Graphics影響因子(影響力)學科排名




書目名稱Image and Graphics網(wǎng)絡公開度




書目名稱Image and Graphics網(wǎng)絡公開度學科排名




書目名稱Image and Graphics被引頻次




書目名稱Image and Graphics被引頻次學科排名




書目名稱Image and Graphics年度引用




書目名稱Image and Graphics年度引用學科排名




書目名稱Image and Graphics讀者反饋




書目名稱Image and Graphics讀者反饋學科排名




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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/461481.jpg
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Conference proceedings 2019and Graphics, ICIG 2019, held in Beijing, China, in August 2019. The 183 full papers presented were selected from 384 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking..
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Measurement-Domain Spiral Predictive Coding for Block-Based Image Compressive Sensingsurement-domain spiral predictive coding method, which can make full use of the intrinsic spatial relationship of natural images. For the measurements of each compressive-sensing block, the optimal measurement prediction is selected from a set of measurement prediction candidates that are generated
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Semantic Map Based Image Compression via Conditional Generative Adversarial Networkhe traditional compression algorithms usually introduce undesired compression artifacts, such as blocking and blurry effects. In this paper, we propose a novel semantic map based image compression framework (SMIC), restoring visually pleasing images at significantly low bit rate. At the encoder, a s
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MHEF-TripNet: Mixed Triplet Loss with Hard Example Feedback Network for Image Retrievalgh. Because of the large imbalance between easy examples and hard examples, networks lack direct guidance information from hard examples. In this paper, we solve the problem by developing an effective and efficient method, called mixed triplet loss with hard example feedback network (MHEF-TripNet).
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