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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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51#
發(fā)表于 2025-3-30 12:11:35 | 只看該作者
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發(fā)表于 2025-3-30 17:47:19 | 只看該作者
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發(fā)表于 2025-3-31 00:28:41 | 只看該作者
Lecture Notes in Networks and Systemsificantly, and tiny objects lack distinguishable appearance information in complex backgrounds, which leads to undesired effects. To solve the issue mentioned above, we propose U-YOLO based on the original YOLOv5 model. We first extend the multi-scale feature fusion network and add a detection head
55#
發(fā)表于 2025-3-31 01:46:14 | 只看該作者
Phoo Phoo Thet Lyar Tun,Chaodit Aswakulsed on this practical problem, the apple fruit images collected from real orchard is taken as the research object, and an improved yolov5s fruit detection model is proposed based on automatic determination of occlusion information. On one hand, an algorithm for automatic judgment based on fruit occl
56#
發(fā)表于 2025-3-31 07:37:26 | 只看該作者
57#
發(fā)表于 2025-3-31 12:58:12 | 只看該作者
https://doi.org/10.1007/978-3-030-64758-2arts of each object instance. Many modern computer vision methods demonstrate excellent performance by using the mechanism of looking and thinking twice and the attention mechanism. In this paper, we propose a feedback attention-augmented bilateral network. Specifically, after the convolutional netw
58#
發(fā)表于 2025-3-31 14:00:49 | 只看該作者
59#
發(fā)表于 2025-3-31 18:43:31 | 只看該作者
Elvira Rodriguez-Rios,Benjamin Garcia-Paezet, a pioneer in point cloud processing, uses max pooling to address the disorder of point clouds. However, PointNet‘s method of mapping points to high-dimensional space, and then obtaining global features through maximum pooling still leads to a large loss of feature information. To this end, we su
60#
發(fā)表于 2025-4-1 01:17:27 | 只看該作者
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