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Titlebook: Neural Information Processing; 26th International C Tom Gedeon,Kok Wai Wong,Minho Lee Conference proceedings 2019 Springer Nature Switzerla

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發(fā)表于 2025-3-21 16:30:44 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Neural Information Processing
副標(biāo)題26th International C
編輯Tom Gedeon,Kok Wai Wong,Minho Lee
視頻videohttp://file.papertrans.cn/664/663608/663608.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Neural Information Processing; 26th International C Tom Gedeon,Kok Wai Wong,Minho Lee Conference proceedings 2019 Springer Nature Switzerla
描述.The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019..The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains.?The second volume, LNCS 11954, is organized in topical sections on image processing by neural techniques; learning from incomplete data; model compression and optimisation; neural learning models; neural network applications; and social network computing..
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; classification; cognitive neurosciences; computational linguistics; computation
版次1
doihttps://doi.org/10.1007/978-3-030-36711-4
isbn_softcover978-3-030-36710-7
isbn_ebook978-3-030-36711-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

書(shū)目名稱Neural Information Processing影響因子(影響力)




書(shū)目名稱Neural Information Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱Neural Information Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Neural Information Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Neural Information Processing被引頻次




書(shū)目名稱Neural Information Processing被引頻次學(xué)科排名




書(shū)目名稱Neural Information Processing年度引用




書(shū)目名稱Neural Information Processing年度引用學(xué)科排名




書(shū)目名稱Neural Information Processing讀者反饋




書(shū)目名稱Neural Information Processing讀者反饋學(xué)科排名




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沙發(fā)
發(fā)表于 2025-3-21 21:50:04 | 只看該作者
Multi-person 3D Pose Estimation from Monocular Image Sequencessidering the temporal smoothness. We evaluate our framework on the Human3.6M dataset and the multi-person image sequence captured by ourselves. The quantitative results on the Human3.6M dataset and the qualitative results on our constructed test data demonstrate the effectiveness of our proposed method.
板凳
發(fā)表于 2025-3-22 01:55:57 | 只看該作者
Shape Description and Retrieval in a Fused Scale Spacee are extracted across scales. Finally, shape retrieval is conducted by an integration of the retrieval results individually yielded at multiple scales. Experimental results on benchmark datasets validate the accuracy, efficiency and robustness of our proposed method.
地板
發(fā)表于 2025-3-22 06:02:48 | 只看該作者
Gated Contiguous Memory U-Net for Single Image Dehazingcombine the features of different levels. We evaluate our proposed method using two public image dehazing benchmarks. The experiments demonstrate that our network can achieve a state-of-the-art performance when compared with other popular methods.
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發(fā)表于 2025-3-22 12:44:28 | 只看該作者
Conference proceedings 2019 different domains.?The second volume, LNCS 11954, is organized in topical sections on image processing by neural techniques; learning from incomplete data; model compression and optimisation; neural learning models; neural network applications; and social network computing..
6#
發(fā)表于 2025-3-22 13:41:13 | 只看該作者
Conference proceedings 2019g, ICONIP 2019, held in Sydney, Australia, in December 2019..The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across
7#
發(fā)表于 2025-3-22 18:12:38 | 只看該作者
0302-9743 Processing, ICONIP 2019, held in Sydney, Australia, in December 2019..The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniq
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發(fā)表于 2025-3-23 04:46:03 | 只看該作者
STNet: A Style Transformation Network for Deep Image Steganographyarbitrary size with 0.06 bit per pixel, improving over other deep steganographic models which only can embed fixed-length secret. Experiment results demonstrate that our STNet can achieve great visual effect, security, and reliability.
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發(fā)表于 2025-3-23 08:52:49 | 只看該作者
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