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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Yijie Pan,Jiayang Guo Conference proceedin

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发表于 2025-3-21 18:22:01 | 显示全部楼层 |阅读模式
期刊全称Advanced Intelligent Computing Technology and Applications
期刊简称20th International C
影响因子2023De-Shuang Huang,Yijie Pan,Jiayang Guo
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Yijie Pan,Jiayang Guo Conference proceedin
影响因子.This 13-volume set LNCS 14862-14874 constitutes - in conjunction with the 6-volume set LNAI 14875-14880 and the two-volume set LNBI 14881-14882 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024...The total of 863 regular papers were carefully reviewed and selected from 2189 submissions...This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology... .
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Mechatronische Fahrwerkregelung,lation experiments, ablation experiments, and generalization experiments. Our model is state-of-the-art and achieves a maximum improvement of 13.07% relative to the baseline on the similar set, particularly on the most challenging novel set with a maximum improvement of 4.06%. In practical experimen
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https://doi.org/10.1007/978-3-8348-9573-8s feature aggregation across multiple scales, particularly benefiting the detection of small objects. We assessed the effectiveness of TC-YOLO on our traffic camera detection dataset, and the results obtained from the experiment substantiate the efficacy of our model. The model attained a mean perfo
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https://doi.org/10.1007/978-3-642-95399-6s. Despite being trained under category supervision, the SGCA module adeptly captures active regions encompassing various high-order semantic features. These features include focusing features and contour features of the object. When integrated into existing lightweight backbone networks, the SGCA m
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https://doi.org/10.1007/978-3-642-95399-6ferent receptive fields and extract multi-scale feature representations. The second is to use the serialized maximum pooling structure to aggregate the local information of the image. By considering the pixels, regions and features around the target, the relationship between the target and its surro
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Vom Kontenrahmen zum Kontenplan,KG with popular adversarial robustness methods. Experiment evaluations on three benchmark databases demonstrate that our proposed attention-aware knowledge guidance for deep metric learning significantly outperforms state-of-the-art defenses in terms of both adversarial robustness and benign perform
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