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Titlebook: Computer Analysis of Images and Patterns; 18th International C Mario Vento,Gennaro Percannella Conference proceedings 2019 Springer Nature

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發(fā)表于 2025-3-28 16:33:15 | 只看該作者
https://doi.org/10.1007/BFb0059240zation, contour evidence extraction, and contour estimation. For the binarization, a model based on the U-Net architecture is trained to convert an input image into its binarized version. The contour evidence extraction starts by recovering contour segments from a binarized image using concave conto
42#
發(fā)表于 2025-3-28 18:54:23 | 只看該作者
MIVIABot: A Cognitive Robot for Smart Museumsetup. Improved robustness and predictable latency is obtained avoiding the use of cloud services in the system..Our robot, that we call MIVIABot, is able to decode and understand speech as well as extract soft biometrics from its interlocutor such as age, gender and emotional status. The robot can
43#
發(fā)表于 2025-3-29 02:53:21 | 只看該作者
How Does Connected Components Labeling with Decision Trees Perform on GPUs?ration does not necessarily apply to every possible scenario. Are we sure that the advantages of decision trees do not compensate for the cost of thread divergence? In order to answer this question, we chose three well-known sequential CCL algorithms, which employ decision trees as the cornerstone o
44#
發(fā)表于 2025-3-29 03:13:49 | 只看該作者
Automated Segmentation of Nanoparticles in BF TEM Images by U-Net Binarization and Branch and Boundzation, contour evidence extraction, and contour estimation. For the binarization, a model based on the U-Net architecture is trained to convert an input image into its binarized version. The contour evidence extraction starts by recovering contour segments from a binarized image using concave conto
45#
發(fā)表于 2025-3-29 09:57:19 | 只看該作者
A Real-Time Processing Stand-Alone Multiple Object Visual Tracking System
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發(fā)表于 2025-3-29 13:57:27 | 只看該作者
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發(fā)表于 2025-3-29 19:03:29 | 只看該作者
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發(fā)表于 2025-3-29 20:07:50 | 只看該作者
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發(fā)表于 2025-3-30 03:25:23 | 只看該作者
50#
發(fā)表于 2025-3-30 04:45:28 | 只看該作者
How Does Connected Components Labeling with Decision Trees Perform on GPUs?pective. In the last decade, many novel algorithms have been released, specifically designed for GPUs. Because CCL literature concerning sequential algorithms is very rich, and includes many efficient solutions, designers of parallel algorithms were often inspired by techniques that had already prov
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