Results 71 to 80 of about 214,708 (186)

»Kde jsou jitra třpytná«

, 2021
Prispevek se ukvarja z zaznamovanostjo leksikalnih enot v prevodih slovenske poezije v češčino. Kot izhodišče za raziskavo izbranega nabora leksemov služijo prevodi del treh slovenskih pesnikov, ki jih je izdelal František Benhart. Na podlagi izsledkov, ki so bili pridobljeni z analizo češkega in slovenskega besedja, avtorica prikazuje možnosti uporabe
openaire   +1 more source

KDE 3.5 is out

, 2005
KDE 3.5 was released with lots of changes. SuperKaramba is now a standard KDE application and is neatly integrated. It allows embedding themelets on your desktop background.
openaire   +2 more sources

Enhancing semantic segmentation in chest X-ray images through image preprocessing: ps-KDE for pixel-wise substitution by kernel density estimation.

PLoS ONE
BackgroundIn medical imaging, the integration of deep-learning-based semantic segmentation algorithms with preprocessing techniques can reduce the need for human annotation and advance disease classification.
Yuanchen Wang, Yujie Guo, Ziqi Wang, Linzi Yu, Yujie Yan, Zifan Gu   +5 more
doaj   +1 more source

Assessing Urban functional area delineation: POI data and kde analysis in pekanbaru

Computational Urban Science
Accurate delineation of urban spatial extent is essential for planning, yet conventional methods based on land cover and satellite imagery are often time-consuming and may lag behind urban changes.
Zahra Witsqa Maghfira, Ridwan Sutriadi, Ahmad Baikuni Perdana   +2 more
doaj   +1 more source

A spatially-informed interpretable deep learning framework for high-resolution nutrient monitoring in complex coastal waters

International Journal of Applied Earth Observations and Geoinformation
Satellite monitoring of non-optically active nutrients remains an ongoing challenge due to their weak spectral signals. While artificial intelligence (AI) methods can improve estimates by incorporating spatiotemporal information, their dependence on ...
Yiqiang Hu, Weikang Zhan, Qingyou He, Yunchen Liu, Haigang Zhan   +4 more
doaj   +1 more source

Traffic density estimation via KDE and nonlinear LS

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2017
With increasing population, the determination of traffic density becomes critical in managing urban city roads for safer driving and low carbon emissions. In this study, kernel density estimation is utilized in order to estimate traffic density more accurately when the speeds of vehicles are available for a given region. For the proposed approach, as a
Yilan, Mikail, Ozdemir, Mehmet Kemal
openaire   +2 more sources

Kde jsou výsledky, kde popis zápasů? Proměna sportovních rubrik v pondělních vydáních českých deníků

Studia sportiva, 2017
The massive development of new media has influenced the traditional media, including the printed daily newspapers. Their sports sections are likely to be affected more than other parts of print media. This article describes the on-going changes and presents the results of an extensive sports journalism research project.
openaire   +3 more sources

Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator

Tongxin xuebao, 2017
For near-field localization of multiple sound sources in reverberant environments,a algorithm model based on approximated kernel density estimator (KDE) was proposed.Multi-stage (MS) of sub-band processing was introduced to effectively solve the spatial ...
Yu-zhuo FANG, Zhi-yong XU, Zhao ZHAO
doaj   +2 more sources

Smart home economic operation under uncertainty: comparing monte carlo and stochastic optimization using gaussian and KDE-based data

Operations Research Perspectives
This paper investigates optimal day-ahead operation of a building-scale energy hub equipped with photovoltaics and a battery. Electricity demand and PV availability are uncertain and are represented in two ways: (i) thin-tailed normal distributions and ...
Spyros Giannelos, Danny Pudjianto, Goran Strbac   +2 more
doaj   +1 more source

Causal Discovery and Reasoning for Continuous Variables with an Improved Bayesian Network Constructed by Locality Sensitive Hashing and Kernel Density Estimation

Entropy
The structure learning of a Bayesian network (BN) is a crucial process that aims to unravel the complex dependencies relationships among variables using a given dataset.
Chenghao Wei, Chen Li, Yingying Liu, Song Chen, Zhiqiang Zuo, Pukai Wang, Zhiwei Ye   +6 more
doaj   +1 more source