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Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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发表于 2025-3-21 19:30:20 | 显示全部楼层 |阅读模式
书目名称Neural Information Processing
副标题30th International C
编辑Biao Luo,Long Cheng,Chaojie Li
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable
描述The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. .The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. .
出版日期Conference proceedings 2024
关键词pattern recognition; affective and cognitive learning; big data; bioinformatics; brain-machine interface
版次1
doihttps://doi.org/10.1007/978-981-99-8073-4
isbn_softcover978-981-99-8072-7
isbn_ebook978-981-99-8073-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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书目名称Neural Information Processing影响因子(影响力)




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书目名称Neural Information Processing网络公开度




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VFIQ: A Novel Model of ViT-FSIMc Hybrid Siamese Network for Image Quality Assessmente-art IQA models in the commonly used correlation metrics of PLCC, KRCC, and SRCC. We also demonstrate the usefulness of our VFIQ model in different vision tasks, such as image recovery and generative model evaluation.
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Conference proceedings 2024ICONIP 2023, held in Changsha, China, in November 2023. .The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, d
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Quantum Autoencoder Frameworks for Network Anomaly Detectionhod; and third a union of a quantum autoencoder and quantum random forest-based method. The quantum frameworks’ effectiveness in accurately detecting the attacks is evaluated using a publicly available benchmark dataset. Our empirical evaluations demonstrate the improvements in accuracy and F1-score for the three frameworks.
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A Frequency Reconfigurable Multi-mode Printed Antennation, good impedance matching (S11 > −10 dB) is obtained in several operating bands, and the overall impedance bandwidth covers 2.34–2.58 GHz and 3.11–5.14 GHz. It provides solutions for operation within WiMax, WLAN, and 5G-sub6 GHz.
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