Improving Indonesian Named Entity Recognition for Domain Zakat Using Conditional Random Fields
JOIN: Jurnal Online Informatika, 2023 In Indonesia, where the majority of the population is Muslim, one of the obligations of a Muslim is zakat. To reduce illiteracy about zakat among Muslims, they need to have access to basic information about it.
Nur Febriana Widiyanti +4 more
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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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Deep Continuous Conditional Random Fields With Asymmetric Inter-Object Constraints for Online Multi-Object Tracking [PDF]
IEEE transactions on circuits and systems for video technology (Print), 2018 Online multi-object tracking (MOT) is a challenging problem and has many important applications including intelligence surveillance, robot navigation, and autonomous driving.
Hui Zhou +4 more
semanticscholar +1 more source
Conditional Random Fields for Pattern Recognition Applied to Structured Data
Algorithms, 2015 Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building ...
Tom Burr, Alexei Skurikhin
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Combined Conditional Random Fields Model for Supervised PolSAR Images Classification
Leida xuebao, 2017 More features and contextual information can be extracted and exploited to improve classification accuracy in complex Polarimetric Synthetic Aperture Radar (PolSAR) imagery classification.
Zou Huanxin +3 more
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Natural Language Processing for Disaster Management Using Conditional Random Fields
Journal of Advances in Information Technology, 2020 This research aims to extract name entity mentioned in unstructured text into a predefined category using Conditional Random Field (CRF) and bidirectional Long Short-Term Memory (LSTM).
H. Ketmaneechairat, Maleerat Maliyaem
semanticscholar +1 more source
Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields [PDF]
IEEE International Conference on Automatic Face & Gesture Recognition, 2017 Automated Facial Expression Recognition (FER) has been a challenging task for decades. Many of the existing works use hand-crafted features such as LBP, HOG, LPQ, and Histogram of Optical Flow (HOF) combined with classifiers such as Support Vector ...
Behzad Hassani, M. Mahoor
semanticscholar +1 more source
Remote Sensing, 2021 In terms of land cover classification, optical images have been proven to have good classification performance. Synthetic Aperture Radar (SAR) has the characteristics of working all-time and all-weather.
Yingying Kong +4 more
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AN UNSUPERVISED SEGMENTATION METHOD FOR REMOTE SENSING IMAGERY BASED ON CONDITIONAL RANDOM FIELDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Segmentation is a fundamental problem in image processing and a common operation in Remote Sensing, which has been widely used especially in Geographic Object-Based Image Analysis (GEOBIA).
A. R. Soares +3 more
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CRaFT: A Conditional Random Fields Toolbox for Matlab
SoftwareXConditional random fields (CRFs) provide a powerful framework for modeling spatial variability while enforcing consistency with measured data, and are essential for uncertainty analysis across a wide range of engineering applications.
Zhibao Zheng
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