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Titlebook: Intelligence Science IV; 5th IFIP TC 12 Inter Zhongzhi Shi,Yaochu Jin,Xiangrong Zhang Conference proceedings 2022 IFIP International Federa

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發(fā)表于 2025-3-21 19:01:57 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligence Science IV
副標(biāo)題5th IFIP TC 12 Inter
編輯Zhongzhi Shi,Yaochu Jin,Xiangrong Zhang
視頻videohttp://file.papertrans.cn/470/469274/469274.mp4
叢書名稱IFIP Advances in Information and Communication Technology
圖書封面Titlebook: Intelligence Science IV; 5th IFIP TC 12 Inter Zhongzhi Shi,Yaochu Jin,Xiangrong Zhang Conference proceedings 2022 IFIP International Federa
描述.This book constitutes the refereed proceedings of the 5th International Conference on Intelligence Science, ICIS 2022, held in Xi‘a(chǎn)n, China, in August 2022.?..The 41 full and 5 short papers presented in this book were carefully reviewed and selected from 85 submissions. They were organized in topical sections as follows: Brain cognition; machine learning; data intelligence; language cognition; remote sensing images; perceptual intelligence; wireless sensor; and medical artificial intelligence..
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; Brain cognition; Brain-computer integration; computer vision; Data Intelligence
版次1
doihttps://doi.org/10.1007/978-3-031-14903-0
isbn_softcover978-3-031-14905-4
isbn_ebook978-3-031-14903-0Series ISSN 1868-4238 Series E-ISSN 1868-422X
issn_series 1868-4238
copyrightIFIP International Federation for Information Processing 2022
The information of publication is updating

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A Memetic Algorithm Based on Adaptive Simulated Annealing for Community Detectionferences to switch to adaptive probabilities in simulated annealing (SA) for local search to accelerate convergence. The algorithm was extensively tested and experimented with 11 artificial and 4 real networks. Compared with other 10 algorithms, the results showed that MA-ASA performs well and is highly competitive.
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Mouse-Brain Topology Improved Evolutionary Neural Network for?Efficient Reinforcement Learningons), but also performed better than other algorithms, including the ENN using a random network, standard long-short-term memory (LSTM), and multi-layer perception (MLP). We think the biologically plausible structures might contribute more to the further development of artificial neural networks.
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Noisy Label Learning in Deep Learninghe problem of learning with label noise from the perspective of supervised learning. And then we will summarize the existing methods from the perspective of dataset usage. Subsequently, we will analyze the problems with the data and existing methods. Finally we will give some possible solution ideas.
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A Simple Approach to the Multiple Source Identification of Information Diffusioning time as diffusion source. Furthermore, we also give a new method to estimate the spreading time which can improve the proposed multiple sources identification algorithm. Simulation results show that the proposed method has distinct advantages in identifying multiple sources in various real-world networks.
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1868-4238 d in topical sections as follows: Brain cognition; machine learning; data intelligence; language cognition; remote sensing images; perceptual intelligence; wireless sensor; and medical artificial intelligence..978-3-031-14905-4978-3-031-14903-0Series ISSN 1868-4238 Series E-ISSN 1868-422X
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