幼儿 发表于 2025-3-23 11:30:33

The method is especially useful for localizing objects in images. Here, we extend the method to the task of joint localization of several objects in a 2D-image by means of combining several centroids. The novel approach, i.e. joint optimization of several centroids and a subsequent optimization of t

BROOK 发表于 2025-3-23 15:16:41

https://doi.org/10.1007/978-1-4020-6454-8Environmental and Hydrologic Time Series; Fourier transform; Hilbert-Huang Transform; Nonstationary Pro

Osteons 发表于 2025-3-23 21:53:09

Water Science and Technology Libraryhttp://image.papertrans.cn/h/image/427078.jpg

dowagers-hump 发表于 2025-3-24 01:25:20

978-90-481-7645-8Springer Science+Business Media B.V. 2008

liaison 发表于 2025-3-24 03:22:29

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思考 发表于 2025-3-24 09:23:59

0921-092X uang transform (HHT) provide an adaptive and efficient method. The HHT is based on the local characteristic time scale of the data. The HHT method provides not only a precise definition in time-frequency representation than the other conventional signal processing methods, but also more physically m

巩固 发表于 2025-3-24 10:46:46

Book 2008form (HHT) provide an adaptive and efficient method. The HHT is based on the local characteristic time scale of the data. The HHT method provides not only a precise definition in time-frequency representation than the other conventional signal processing methods, but also more physically meaningful

危机 发表于 2025-3-24 15:32:54

oral Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ‘dead’ rules. Also

exorbitant 发表于 2025-3-24 20:23:06

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hermetic 发表于 2025-3-25 00:33:16

A. Ramachandra Rao,En-Ching Hsud to diversify existing data as to improve lacking datasets, and data privacy, as the generated data, while next to real, can be shared without the original, protected model. A case study was done in an industry-recognized benchmark model, and the results completely support the use of the proposed m
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查看完整版本: Titlebook: Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series; A. Ramachandra Rao,En-Ching Hsu Book 2008 Springer Science