Titlebook: Intelligent Human Computer Interaction; 15th International C Bong Jun Choi,Dhananjay Singh,Wan-Young Chung Conference proceedings 2024 The

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书目名称Intelligent Human Computer Interaction影响因子(影响力)




书目名称Intelligent Human Computer Interaction影响因子(影响力)学科排名




书目名称Intelligent Human Computer Interaction网络公开度




书目名称Intelligent Human Computer Interaction网络公开度学科排名




书目名称Intelligent Human Computer Interaction被引频次




书目名称Intelligent Human Computer Interaction被引频次学科排名




书目名称Intelligent Human Computer Interaction年度引用




书目名称Intelligent Human Computer Interaction年度引用学科排名




书目名称Intelligent Human Computer Interaction读者反馈




书目名称Intelligent Human Computer Interaction读者反馈学科排名

脆弱吧

978-3-031-53826-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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ONYM

https://doi.org/10.1007/978-3-031-53827-8Human-Computer Interaction (HCI); computer security; human engineering; telecommunication systems; artif

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Conference proceedings 2024ors, Human Centred AI, Human-Robot Interaction and Intelligent Interfaces and User Centred Design..Volume II: AI and Big Data, Deep Learning, Intelligent Systems, Mobile Computing and Ubiquitous Interactions and Social Computing and Interactive Elements..

vocation

0302-9743 Human Factors, Human Centred AI, Human-Robot Interaction and Intelligent Interfaces and User Centred Design..Volume II: AI and Big Data, Deep Learning, Intelligent Systems, Mobile Computing and Ubiquitous Interactions and Social Computing and Interactive Elements..978-3-031-53826-1978-3-031-53827-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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0302-9743 ld in Daegu, South Korea, during November 8–10, 2023..The 55 full papers and 16 short papers included in this book were carefully reviewed and selected from 139 submissions. They were organized in topical sections as follows: .Volume I: Natural Language and Dialouge Systems, Affective Computing and

轨道

HGAN: Editable Visual Generation from Hindi Descriptionsre diversity, word-level spatial attention and channel-wise attention mechanisms are employed to enable the model to offer control over the attributes of generated content. HGAN shows considerably good results, a 20.3% increase in IS and a 16.6% decrease in reconstruction error on the Hindi dataset than state-of-the-art methods.

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