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Titlebook: Computational Science and Its Applications – ICCSA 2021; 21st International C Osvaldo Gervasi,Beniamino Murgante,Carmelo Maria T Conference

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21#
發(fā)表于 2025-3-25 05:44:48 | 只看該作者
https://doi.org/10.1007/978-3-540-46853-0iating sensor-specific processing pipelines in sensor-heterogeneous environments. Motivated by shortcomings of the photo response non-uniformity (PRNU) based method in the biometric context, we employ eight texture classification approaches, including frequency-, spatial-, and wavelet-based methods
22#
發(fā)表于 2025-3-25 10:33:34 | 只看該作者
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發(fā)表于 2025-3-25 12:10:17 | 只看該作者
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發(fā)表于 2025-3-25 16:06:13 | 只看該作者
25#
發(fā)表于 2025-3-25 22:20:42 | 只看該作者
Deep Learning for Accurate Corner Detection in Computer Vision-Based Inspectionoped for the worker training and assessment. In our local built and construction industry, workers need to be certified for their technical skills through a training and assessment process. Assessment involves trainees to understand a task given with a technical drawing, e.g. electrical wiring and t
26#
發(fā)表于 2025-3-26 03:52:34 | 只看該作者
27#
發(fā)表于 2025-3-26 07:13:21 | 只看該作者
The Importance of Color Spaces for Image Classification Using Artificial Neural Networks: A Reviework, when implementing ANN-based image classification models, the images used for training and testing are always represented in the RGB color space. But recent articles show that the use of certain color spaces, other than RGB, can lead to better precision in ANN-based image classification models.
28#
發(fā)表于 2025-3-26 10:40:43 | 只看該作者
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發(fā)表于 2025-3-26 13:45:24 | 只看該作者
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