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Titlebook: Computer Vision Systems; 12th International C Dimitrios Tzovaras,Dimitrios Giakoumis,Antonis Arg Conference proceedings 2019 Springer Natur

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發(fā)表于 2025-3-25 04:12:07 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234033.jpg
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發(fā)表于 2025-3-25 07:57:29 | 只看該作者
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發(fā)表于 2025-3-25 11:54:25 | 只看該作者
24#
發(fā)表于 2025-3-25 17:42:14 | 只看該作者
A Short Introduction to Statistics,figurations that optimize a local shape complementarity metric. We validate the proposed approach in MuJoCo physics engine. Our experiments show that the explicit consideration of shape complementarity of the hand leads to robust grasping of unknown objects.
25#
發(fā)表于 2025-3-25 20:09:28 | 只看該作者
0302-9743 ision assisted systems for energy awareness and behavior analysis; and vision-enabled UAV and counter UAV technologies for surveillance and security of critical infrastructures..978-3-030-34994-3978-3-030-34995-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
26#
發(fā)表于 2025-3-26 02:43:14 | 只看該作者
The Decentralized Energy Revolutionnvolution and binary weights. Besides, we also use SIMD (Single Instruction Multiple Data) to accelerate the operations. Full procedure and net structure have been given in this paper. Experimental results show that the proposed CNN architecture can run at full frame rate (140 Fps on CPU) with an accurate percentage of 97.13%.
27#
發(fā)表于 2025-3-26 07:18:21 | 只看該作者
28#
發(fā)表于 2025-3-26 10:25:41 | 只看該作者
The Decision to Delist from the Stock Marketnnel. The efficacy of the proposed framework has been evaluated in multiple experimental field trials in an underground mine in Sweden, thus demonstrating the capability of low-cost and resource-constrained aerial vehicles to fly autonomously through tunnel confined spaces.
29#
發(fā)表于 2025-3-26 13:34:55 | 只看該作者
30#
發(fā)表于 2025-3-26 16:52:44 | 只看該作者
Real-Time Lightweight CNN in Robots with Very Limited Computational Resources: Detecting Ball in NAOnvolution and binary weights. Besides, we also use SIMD (Single Instruction Multiple Data) to accelerate the operations. Full procedure and net structure have been given in this paper. Experimental results show that the proposed CNN architecture can run at full frame rate (140 Fps on CPU) with an accurate percentage of 97.13%.
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