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Titlebook: Cognitive Computation and Systems; First International Fuchun Sun,Jianmin Li,Zhongyi Chu Conference proceedings 2023 The Editor(s) (if app

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21#
發(fā)表于 2025-3-25 05:51:25 | 只看該作者
Feedback Attention-Augmented Bilateral Network for?Amodal Instance Segmentationch and the spatial branch. We achieve better results on COCOA dataset and D2SA dataset. For COCOA dataset, our method outperforms different state-of-the-art models by 1.2% and 1.6% mAP under “All regions” and “Things only”, and brings 9.4% improvement on D2SA dataset.
22#
發(fā)表于 2025-3-25 09:14:09 | 只看該作者
A Fusion Method for 2D LiDAR and RGB-D Camera Depth Image Without Calibratione dataset: a widely recognized in-doors open robot navigation database. The results show that the proposed method contributes to de-noise of the original data both for 2D LiDAR and RGB-D depth image simultaneously. The proposed method is also validated on the realistic navigation environments, and i
23#
發(fā)表于 2025-3-25 15:00:13 | 只看該作者
24#
發(fā)表于 2025-3-25 19:34:18 | 只看該作者
25#
發(fā)表于 2025-3-25 22:55:25 | 只看該作者
26#
發(fā)表于 2025-3-26 00:35:30 | 只看該作者
Cognitive Computing and System Analysis of Seven Times Pass Method Applications and Its Significancehe seven-pass application, and further enrich the teaching and learning practice. The way in which the management practice is active. The significance is that this not only has a positive effect on the teaching, review and examination quality of national education system at all levels, but also has
27#
發(fā)表于 2025-3-26 07:52:00 | 只看該作者
Cognitive Computing and Systems Analysis of Alumni Economic Theory and Practiceomic theory and practice. The results are beneficial for the economic practice of domestic and foreign alumni to further rise to the height of theoretical research, and to achieve sufficient interpersonal communication and high interpersonal collaboration. Its significance lies in: Chinese and forei
28#
發(fā)表于 2025-3-26 09:57:03 | 只看該作者
29#
發(fā)表于 2025-3-26 12:47:16 | 只看該作者
30#
發(fā)表于 2025-3-26 18:56:59 | 只看該作者
Lecture Notes in Networks and Systemsot only improves the detection performance on drone-captured scenarios but also has a real-time detection speed. Compared to baseline model (YOLOv5s), the mAP result of U-YOLO is increased from 19.07 to 24.1%, and the detection speed is 39FPS. It provides a good balance between detection accuracy an
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