Monocle
发表于 2025-3-25 04:06:01
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BULLY
发表于 2025-3-25 10:48:06
Rituparna Chaki,Nabendu Chaki,Khalid SaeedDiscusses recent research trends in computational intelligence.Presents applications to design, analysis, and modeling – key areas in computational intelligence.Explores efficient computational algori
小教堂
发表于 2025-3-25 12:21:45
Lecture Notes in Networks and Systemshttp://image.papertrans.cn/a/image/145395.jpg
Lacunar-Stroke
发表于 2025-3-25 17:51:14
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Cpr951
发表于 2025-3-25 21:23:13
https://doi.org/10.1057/9781137272867s (such as MPICH and Open MPI) have been broadly used in the high-performance computing area to provide efficient data processing. This paper investigates whether MPI can be adapted to a batch processing task in the field of image processing which has the characteristic of input and output data in t
Atmosphere
发表于 2025-3-26 00:55:53
https://doi.org/10.1057/9781137272867with some added advantages like heterogeneous integration, higher computation per volume, etc. These benefits are also exhibited in 3D SoCs (3D System on Chips) to use the already built cores. However, testing these large complex SoCs in lesser time has become a challenge. In this paper, we propose
表脸
发表于 2025-3-26 04:36:20
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悠然
发表于 2025-3-26 12:30:15
J. J. de la Rosette,F. M. Debruyned. Firstly, the images are pre-processed for further tasks which are followed by the extraction of morphological and amplitude-based features. The best discriminatory features are chosen by applying several feature selection techniques which evaluate the merit of a feature by assessing the goodness
大方不好
发表于 2025-3-26 15:08:25
Klinische Diagnostik und PCA-Screeninguracy guaranteed by this measurable trait. In the literature, one can easily find diversified approaches and algorithms connected with this feature, however, neither of them uses discrete fast Fourier transform to describe iris sample. In this work, the authors used recently mentioned method to crea
LAVA
发表于 2025-3-26 16:53:10
Klaus Höfner,Udo Jonas,Christian G. Stiefby them is maximized. In general, the performance of an influence maximization algorithm is measured in terms of solution accuracy and computational efficiency. Simulation-based greedy algorithms can achieve high solution accuracy but are inappropriate for large networks owing to their huge computat