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Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning [PDF]
Sensors, 2017 Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT).
Ehwa Yang, Jeonghwan Gwak, Moongu Jeon
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Conditional Random Field-Guided Multi-Focus Image Fusion
Journal of Imaging, 2022 Multi-Focus image fusion is of great importance in order to cope with the limited Depth-of-Field of optical lenses. Since input images contain noise, multi-focus image fusion methods that support denoising are important.
Odysseas Bouzos +2 more
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EFFICIENT SEMANTIC SEGMENTATION OF MAN-MADE SCENES USING FULLY-CONNECTED CONDITIONAL RANDOM FIELD [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 In this paper we explore semantic segmentation of man-made scenes using fully connected conditional random field (CRF). Images of man-made scenes display strong contextual dependencies in the spatial structures. Fully connected CRFs can model long-range
W. Li, M. Y. Yang, M. Y. Yang
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Rockhead profile simulation using an improved generation method of conditional random field
Journal of Rock Mechanics and Geotechnical Engineering, 2022 Rockhead profile is an important part of geological profiles and can have significant impacts on some geotechnical engineering practice, and thus, it is necessary to establish a useful method to reverse the rockhead profile using site investigation ...
Liang Han +4 more
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IEEE Access, 2021 Weaponry equipment names belong to an important military naming entity that is difficult to identify because of features, such as complex components, miscellaneous, and scarce annotation corpus. Here, the automatic recognition of weaponry equipment names
Chenguang Liu +3 more
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Chinese Sequence Labeling Based on Stack Pre-training Model
Journal of Harbin University of Science and Technology, 2022 Sequence labeling is an important task in natural language processing. In this paper, according to the relevance of tasks, we use stacking pretraining model to extract features, segment words, and name entity recognition/chunk tagging.Through in-depth ...
LIU Yu-peng, LI Guo-dong
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Scene-Layout Compatible Conditional Random Field for Classifying Terrestrial Laser Point Clouds [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 Terrestrial Laser Scanning (TLS) rapidly becomes a primary surveying tool due to its fast acquisition of highly dense threedimensional point clouds. For fully utilizing its benefits, developing a robust method to classify many objects of interests from ...
C. Luo, G. Sohn
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IEEE Access, 2021 Many electrical equipment malfunction text messages are collected during power system operation and maintenance procedures. These texts usually contain crucial information for maintenance and condition monitoring.
Zhe Kong +5 more
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Study on MRI Medical Image Segmentation Technology Based on CNN-CRF Model
IEEE Access, 2020 Image segmentation is an important technique for segmenting images without overlapping each other and having their own features. It has been rapidly developed in the field of medical imaging, but there is currently a difference between classification ...
Naiqin Feng, Xiuqin Geng, Lijuan Qin
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MULTITEMPORAL CROP TYPE CLASSIFICATION USING CONDITIONAL RANDOM FIELDS AND RAPIDEYE DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM).
T. Hoberg, S. Müller
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