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Titlebook: 2nd EAI International Conference on Robotic Sensor Networks; ROSENET 2018 Huimin Lu,Li Yujie Conference proceedings 2020 Springer Nature Sw

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41#
發(fā)表于 2025-3-28 15:38:36 | 只看該作者
42#
發(fā)表于 2025-3-28 22:44:00 | 只看該作者
Conference proceedings 2020erence on Robotic Sensor Networks. The conference explores the integration of networks and robotic technologies, which has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. The authors posit that big networks will be the main app
43#
發(fā)表于 2025-3-29 00:54:43 | 只看該作者
44#
發(fā)表于 2025-3-29 04:27:01 | 只看該作者
Der grosse P?bel- und Sklavenaufstandsually use such as the wavelet transform fusion method, the PCA transform fusion method, and the Gram–Schmidt transform fusion method. The experimental results show that the spatial information is better than the other three methods in terms of spatial details and texture.
45#
發(fā)表于 2025-3-29 07:24:52 | 只看該作者
https://doi.org/10.1007/978-3-476-03498-4we remove the haze, which is caused by turbidity of water, from image. After its process, we apply “YOLO” to tracking and recognizing the marine organisms, which includes shrimp, squid, crab, and shark. Our developed system shows generally satisfactory performance.
46#
發(fā)表于 2025-3-29 14:05:17 | 只看該作者
https://doi.org/10.1007/978-3-476-03498-4C algorithm with an improved scout bee strategy. Different from the traditional scout bee strategy, we use a local search strategy when a bee stagnates for a defined value. The experimental results on Berkeley segmentation database demonstrate the effectiveness of our algorithm.
47#
發(fā)表于 2025-3-29 18:09:01 | 只看該作者
48#
發(fā)表于 2025-3-29 22:17:32 | 只看該作者
,Im Garten der (mathematischen) Lüste, sorted candidate set is built by using LSH; on this basis, the near-duplicate videos are cleaned by using the SNM. Finally, the simulation experiments are implemented to show that the presented method in this chapter is effective, which can be used to clean near-duplicate videos automatically and improve video data quality.
49#
發(fā)表于 2025-3-30 02:05:04 | 只看該作者
50#
發(fā)表于 2025-3-30 05:13:01 | 只看該作者
,Stand der Forschung und Resümee,ompare it with other task allocation methods based on classic Hungarian algorithm. In the experiments, we analyze the impact of the number of tasks and robots on the running time and robustness of the methods. The results suggest that our solution outperforms others, that is, robots can accomplish tasks faster and more effectively.
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