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Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Xiankun Zhang,Chuanlei Zhang Conference pr

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樓主: 小費
41#
發(fā)表于 2025-3-28 15:11:05 | 只看該作者
42#
發(fā)表于 2025-3-28 22:04:09 | 只看該作者
43#
發(fā)表于 2025-3-29 01:04:30 | 只看該作者
44#
發(fā)表于 2025-3-29 05:44:08 | 只看該作者
Der Inhalt der Marktbeobachtunghe complexity and unpredictability of unknown environments pose great difficulties for decision-making in search and rescue phases, ultimately resulting in serious consequences. To address the decision-making problems, this paper proposes a hierarchical swarm robots digital twin framework, which inc
45#
發(fā)表于 2025-3-29 08:22:34 | 只看該作者
https://doi.org/10.1007/978-3-663-02526-9efficient and reliable path planning. This study addresses the critical intersection of path planning and energy efficiency in USVs, focusing on the challenge of navigating dynamic oceanic environments while minimizing energy consumption. Building upon our previous work, which developed an energy-ef
46#
發(fā)表于 2025-3-29 13:51:48 | 只看該作者
47#
發(fā)表于 2025-3-29 19:16:20 | 只看該作者
Die Verfahren der Marktbeobachtungurate state representation and efficient task planning. In the field of robotics, both contingent planning and probabilistic planning have proven effective in generating robust plans under such conditions. However, as the scale of the problem escalates, these approaches inevitably yield numerous red
48#
發(fā)表于 2025-3-29 20:11:04 | 只看該作者
Der Gegenstand der Marktbeobachtung The model integrates a new ConvNeXt convolutional layer structure and a wide receptive field module, incorporating techniques such as inverted bottleneck layers, GELU activation functions, and layer normalization. Additionally, it introduces a parameter-free attention module (SimAM) to enhance netw
49#
發(fā)表于 2025-3-30 02:10:59 | 只看該作者
Der Gegenstand der Marktbeobachtung robotics. Validated on a real-world underwater biological dataset, the model maintains YOLOv7‘s high detection efficiency and stability while significantly reducing inference speed and parameters, meeting real-time requirements on edge devices. Contributions include introducing Mobile One‘s re-para
50#
發(fā)表于 2025-3-30 06:28:02 | 只看該作者
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