全部文献期刊学位论文会议报纸专利标准年鉴图书|学者科研项目
中外文文献  中文文献  外文文献
作者:Chang-Tsun Li , Xufeng Lin
来源:[J].EURASIP Journal on Image and Video Processing(IF 0.57), 2017, Vol.2017 (1)Springer
摘要:... During this process, each SPN is treated as a random variable and a Markov random field (MRF) approach is employed to iteratively assign a class label to each SPN (i.e., random variable). The clustering process requires no a priori knowledge about the dataset from the us...
作者:Chan-Seok Jeong , Dongsup Kim
来源:[J].BMC Bioinformatics(IF 3.024), 2016, Vol.17 (1)Springer
摘要:... Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by foc...
作者:BoLin Chen , Min Li , JianXin Wang ...
来源:[J].Science China Life Sciences(IF 2.024), 2014, Vol.57 (11), pp.1054-1063Springer
摘要:... To capture the gene-disease associations based on biological networks, a kernel-based MRF method is proposed by combining graph kernels and the Markov random field (MRF) method. In the proposed method, three kinds of kernels are employed to describe the overall relationships ...
作者:Xiangyong Cao , Zongben Xu , Deyu Meng
来源:[J].Remote Sensing(IF 2.101), 2019, Vol.11 (13)DOAJ
摘要:... Finally, the classification map is processed by Markov random field (MRF) in order to further utilize the smoothness property of the labels. To ease experimental comparison for different HSI classification methods, we built an open package to make the comparison fairly and ef...
作者:Haoyang Yu , Lianru Gao , Jun Li ...
来源:[J].Remote Sensing(IF 2.101), 2016, Vol.8 (4)DOAJ
摘要:... Then, the spatial information of the image pixels is modeled using an adaptive Markov random field (MRF) method. Finally, the maximum posterior probability classification is computed via the simulated annealing (SA) optimization algorithm. The combination of subspace-based SV...
作者:Wei Gu , Zhihan Lv , Ming Hao
来源:[J].Multimedia Tools and Applications(IF 1.014), 2017, Vol.76 (17), pp.17719-17734Springer
摘要:The fixed weights between the center pixel and neighboring pixels are used in the traditional Markov random field for change detection, which will easily cause the overuse of spatial neighborhood information. Besides the traditional label field cannot accurately identify the spat...
作者:Alexandre Levada
来源:[J].Entropy(IF 1.347), 2014, Vol.16 (2), pp.1002-1036DOAJ
摘要:Markov random field models are powerful tools for the study of complex systems. However, little is known about how the interactions between the elements of such systems are encoded, especially from an information-theoretic perspective. In this paper, our goal is to enlighten the...
作者:Apisit Eiumnoh , Preesan Rakwatin , Ratchawit Sirisommai ...
来源:[J].Remote Sensing(IF 2.101), 2013, Vol.5 (10), pp.5089-5121DOAJ
摘要:... In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF) model to simultaneously align two or more images and obtain a land cover map (LCM) of the scene. The expectation maximization (EM) algorithm is employed to solve t...
作者:Hongju Cheng , Zhihuang Su , Jaime Lloret ...
来源:[J].Sensors(IF 1.953), 2014, Vol.14 (11), pp.20940-20962DOAJ
摘要:... We firstly introduce how to model the data correlation for different services by using Markov Random Field (MRF) model. Secondly, we formulate the service-oriented node scheduling issue into three different problems, namely, the multi-service data denoising problem which aims...
作者:Thierry Géraud , Jean-Baptiste Mouret
来源:[J].EURASIP Journal on Advances in Signal Processing(IF 0.807), 2004, Vol.2004 (16), pp.1-12Springer
摘要:...gif" Format="GIF" Rendition="HTML" Type="Linedraw"/> Markov random fields" to the extraction of curvilinear objects. Many road extractors which are composed of two stages can be found in the literature. The first one acts like a filter that can decide from a local analysis, at...

我们正在为您处理中,这可能需要一些时间,请稍等。

资源合作:cnki.scholar@cnki.net, +86-10-82896619   意见反馈:scholar@cnki.net

×