Results 31 to 40 of about 9,325,572 (289)
Reversing conditional orderings [PDF]
, 2013 We analyze some specific aspects concerning conditional orderings and relations among them. To this purpose we define a suitable concept of reversed conditional ordering and prove some related results.
Fabio Spizzichino +3 more
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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
HIERARCHICAL CONDITIONAL RANDOM FIELD FOR MULTI-CLASS IMAGE CLASSIFICATION [PDF]
, 2010 Multi-class image classification has made significant advances in recent years through the combination of local and global features. This paper proposes a novel approach called hierarchical conditional random field (HCRF) that explicitly models region ...
Drauschke, Martin +2 more
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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
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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
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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
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Conditional Variable Importance for Random Forests [PDF]
, 2008 Random forests are becoming increasingly popular in many scientific fields because they can cope with ``small n large p'' problems, complex interactions and even highly correlated predictor variables. Their variable importance measures have recently been
Augustin Thomas +14 more
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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
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Conditional Random Fields for Metaphor Detection [PDF]
Proceedings of the Workshop on Figurative Language Processing, 2018 We present an algorithm for detecting metaphor in sentences which was used in Shared Task on Metaphor Detection by First Workshop on Figurative Language Processing. The algorithm is based on different features and Conditional Random Fields.
Anna Mosolova +2 more
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Conditional random fields for activity recognition [PDF]
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, 2007 Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we compare two models for temporal classification: hidden Markov models (HMMs), which have long been applied to the activity recognition problem, and conditional random fields ...
Douglas L. Vail +2 more
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