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Titlebook: Cognitive Computing – ICCC 2021; 5th International Co Ruifeng Xu,Cheng Cai,Liang-Jie Zhang Conference proceedings 2022 Springer Nature Swit

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發(fā)表于 2025-3-21 18:23:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Cognitive Computing – ICCC 2021
副標(biāo)題5th International Co
編輯Ruifeng Xu,Cheng Cai,Liang-Jie Zhang
視頻videohttp://file.papertrans.cn/230/229016/229016.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Cognitive Computing – ICCC 2021; 5th International Co Ruifeng Xu,Cheng Cai,Liang-Jie Zhang Conference proceedings 2022 Springer Nature Swit
描述This book constitutes the proceedings of the International Conference on Cognitive Computing, ICCC 2021, held as part of SCF 2021 in December 2021. The conference was held virtually due to the COVID-19 pandemic.. The 5 full and 3 short papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers cover all aspects of Sensing Intelligence (SIJ as a Service (SlaaS). Cognitive Computing is a sensing-driven computing (SDC) scheme that explores and integrates intelligence from all types of senses in various scenarios and solution contexts.
出版日期Conference proceedings 2022
關(guān)鍵詞action recognition; artificial intelligence; computer hardware; computer science; computer vision; educat
版次1
doihttps://doi.org/10.1007/978-3-030-96419-1
isbn_softcover978-3-030-96418-4
isbn_ebook978-3-030-96419-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2022
The information of publication is updating

書目名稱Cognitive Computing – ICCC 2021影響因子(影響力)




書目名稱Cognitive Computing – ICCC 2021影響因子(影響力)學(xué)科排名




書目名稱Cognitive Computing – ICCC 2021網(wǎng)絡(luò)公開度




書目名稱Cognitive Computing – ICCC 2021網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Cognitive Computing – ICCC 2021被引頻次




書目名稱Cognitive Computing – ICCC 2021被引頻次學(xué)科排名




書目名稱Cognitive Computing – ICCC 2021年度引用




書目名稱Cognitive Computing – ICCC 2021年度引用學(xué)科排名




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書目名稱Cognitive Computing – ICCC 2021讀者反饋學(xué)科排名




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Contrastive Learning for Multiple Models in One Supernet It is empowered by the way that AMLs means to adjust among stability and plasticity of a learning system. At present, deep learning-based unsupervised learning is another intriguing issue in the field of Autonomous Machine Learning, among which multi-architecture optimization is of extraordinary tr
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The WeChat Mini-program for Oral English Evaluation Based on the Smart Listening Algorithmand divide students into different levels, which can accurately return students’ oral English scores and other details in real time. A typical feature of this algorithm is that it supports voice evaluation covering all ages from children to adults, with multiple modes such as words, sentences, parag
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Constant Force Drawing of Chemical Fibersther knitted clothing, chemical fibers fabrics are widely used. Hence, their quality directly affects the quality of clothes. If the endurance and toughness of chemical fibers are not good enough, the clothes will wrinkle easily, which will in turn affect the look and quality of the clothes. For che
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Conversational Humor Identification Based on?Adversarial Learning on?Chinese Sitcomsmor identification is to identify the punchline. To do this, we propose a humor identification model based on Adversarial Learning, where the generator is able to produce sequences similar to punchlines, while the discriminator can learn the features to distinguish punchlines from non-humor dialogue
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