Results 31 to 40 of about 438,874 (275)
Analogues of Non-Gibbsianness in Joint Measures of Disordered Mean Field Models [PDF]
, 2002 It is known that the joint measures on the product of spin-space and disorder space are very often non-Gibbsian measures, for lattice systems with quenched disorder, at low temperature.
Külske, Christof,
core +3 more sources
Bearing Fault Classification Based on Conditional Random Field
Shock and Vibration, 2013 Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment.
Guofeng Wang, Xiaoliang Feng, Chang Liu
doaj +1 more source
Quantifying uncertainties on excursion sets under a Gaussian random field prior [PDF]
, 2016 We focus on the problem of estimating and quantifying uncertainties on the excursion set of a function under a limited evaluation budget. We adopt a Bayesian approach where the objective function is assumed to be a realization of a Gaussian random field.
Azzimonti, Dario +3 more
core +5 more sources
Research of ddi based on multi-label conditional random field
BIO Web of Conferences, 2017 The detection of drug name and drug-drug interaction(DDI) is considered as a sequence labeling task in this paper. We present the multi-label CRF method to complete it.
Yu Yangzhi, Deng Hongtao, Zhu Xun
doaj +1 more source
Source-Device-Independent Ultrafast Quantum Random Number Generation [PDF]
, 2017 Secure random numbers are a fundamental element of many applications in science, statistics, cryptography and more in general in security protocols.
MARANGON, DAVIDE GIACOMO +2 more
core +1 more source
Shallow parsing with conditional random fields [PDF]
Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03, 2003 Conditional random fields for sequence labeling offer advantages over both generative models like HMMs and classifiers applied at each sequence position. Among sequence labeling tasks in language processing, shallow parsing has received much attention, with the development of standard evaluation datasets and extensive comparison among methods.
Fei Sha, Fernando C. N. Pereira
openaire +2 more sources
MULTI-SOURCE MULTI-SCALE HIERARCHICAL CONDITIONAL RANDOM FIELD MODEL FOR REMOTE SENSING IMAGE CLASSIFICATION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Fusion of remote sensing images and LiDAR data provides complimentary information for the remote sensing applications, such as object classification and recognition.
Z. Zhang, M. Y. Yang, M. Zhou
doaj +1 more source
Linear street extraction using a Conditional Random Field model [PDF]
, 2015 A novel method for extracting linear streets from a street network is proposed where a linear street is defined as a sequence of connected street segments having a shape similar to a straight line segment.
Bertolotto, Michela +2 more
core +2 more sources
Image Labeling with Markov Random Fields and Conditional Random Fields
CoRR, 2018 Most existing methods for object segmentation in computer vision are formulated as a labeling task. This, in general, could be transferred to a pixel-wise label assignment task, which is quite similar to the structure of hidden Markov random field. In terms of Markov random field, each pixel can be regarded as a state and has a transition probability ...
Shangxuan Wu, Xinshuo Weng
openaire +2 more sources
, 2014 In this paper, we consider the extreme behavior of a Gaussian random field $f(t)$ living on a compact set $T$. In particular, we are interested in tail events associated with the integral $\int_Te^{f(t)}\,dt$.
Liu, Jingchen, Xu, Gongjun
core +1 more source