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Segment-based hidden Markov models for information extraction

Zhenmei Gu, Nick Cercone
2006 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL - ACL '06  
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE).  ...  We propose to use HMMs to model text at the segment level, in which the extraction process consists of two steps: a segment retrieval step followed by an extraction step.  ...  Introduction A Hidden Markov Model (HMM) is a finite state automaton with stochastic state transitions and symbol emissions (Rabiner, 1989) .  ... 
doi:10.3115/1220175.1220236 dblp:conf/acl/GuC06 fatcat:ccali336knerfcxoeynep2o23q

Multiscale Information Fusion by Graph Cut through Convex Optimization [chapter]

Yinhui Zhang, Yunsheng Zhang, Zifen He
2010 Lecture Notes in Computer Science  
This paper proposed a novel method for global continuous optimization of maximum a posterior(MAP) during wavelet-domain hidden Markov tree-based(WHMT) multiscale information fusion process.  ...  A performance measure for tobacco leaf inspection is used to evaluate our algorithm, the localization accuracy of weak boundary by fusing multiscale information via convex optimization is encouraging.  ...  Ref. [1] proposed a kind of hidden Markov model which is called hidden Markov tree for statistical in wavelet domain.  ... 
doi:10.1007/978-3-642-17277-9_39 fatcat:uq5ngrhjpjc3xnmegggsqw57e4

Off-line Cursive Handwritten Tamil Character Recognition

R. Jagadeesh Kannan, R. Prabhakar, R. M. Suresh
2008 2008 International Conference on Security Technology  
The approach utilizes discrete Hidden Markov Models (HMMs) for recognizing off-line cursive handwritten Tamil characters.  ...  In spite of several advancements in technologies pertaining to Optical character recognition, handwriting continues to persist as means of documenting information for day-to-day life.  ...  Hidden Markov Model Hidden Markov Models are suitable for handwriting recognition for a number of reasons [10] .  ... 
doi:10.1109/sectech.2008.33 fatcat:shcmjyb46veinnl6vyfn4sgfcq

Markovian Segmentation of Brain Tumor MRI Images

Meryem Ameur, Cherki Daoui, Najlae Idrissi
2017 International Journal of Informatics and Communication Technology (IJ-ICT)  
These algorithms are used to segment brain tumor Magnetic Resonance Imaging (MRI) images, under Hidden Markov Chain with Indepedant Noise (HMC-IN).  ...  <p>Image segmentation is a fundamental operation in image processing, which consists to di-vide an image in the homogeneous region for helping a human to analyse image, to diagnose a disease and take the  ...  Our study focuses on a classical hidden Markov chain model to segment the brain tumor MRI images. Hidden Markov model models the image Y according to the selected model (field, chain, tree).  ... 
doi:10.11591/ijict.v6i3.pp155-165 fatcat:aadysvicbjebfhl6hfikp6qceq

Off-Line Arabic Handwritten Characters Recognition Based on a Hidden Markov Models [chapter]

M. Amrouch, M. Elyassa, A. Rachidi, D. Mammass
2008 Lecture Notes in Computer Science  
We present a system based on Hidden Markov Models (HMMs) for offline isolated Arabic handwritten characters recognition.  ...  This information is translated into sequences of observations that are used to train the model for each character during the learning step.  ...  Hidden Markov Models ( HMMs) A Hidden Markov Model is a double stochastic process with an underlying process which is not observable.  ... 
doi:10.1007/978-3-540-69905-7_51 fatcat:t4y267wg6bb2zmwwtwww3dn7ly

Ottoman Script Recognition Using Hidden Markov Model

Ayşe Onat, Ferruh Yildiz, Mesut Gündüz
2008 Zenodo  
The output of segmentation is well-defined segments that can be fed into any classification approach. The classes of main strokes are identified through left-right Hidden Markov Model (HMM).  ...  In this study, an OCR system for segmentation, feature extraction and recognition of Ottoman Scripts has been developed using handwritten characters.  ...  HIDDEN MARKOV MODELS Hidden Markov Models (HMMs) are finite state machines and powerful statistical models for modeling sequential or time-series data, and have been successfully used in many tasks such  ... 
doi:10.5281/zenodo.1059657 fatcat:sn7osfg6svdrvmtxq6o2vxcpt4

Background Speech Synchronous Recognition Method of E-commerce Platform Based on Hidden Markov Model

Pei Jiang, Dongchen Wang
2022 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
on Hidden Markov model.  ...  Finally, the experimental results show that the background speech synchronous recognition method based on Hidden Markov model is better than the traditional methods.  ...  Based on this, the hidden Markov model is used for framing, because the hidden Markov model has less spectrum leakage.  ... 
doi:10.46300/9106.2022.16.42 fatcat:nhbrtmqj3vantjvtyhxlvlrwcq

Image segmentation approach to extract colon lumen through colonic material tagging and hidden Markov random field model for virtual colonoscopy

Lihong Li, Dongqing Chen, Sarang Lakare, Kevin Kreeger, Ingmar Bitter, Arie E. Kaufman, Mark R. Wax, Petar M. Djuric, Zhengrong Liang, Anne V. Clough, Chin-Tu Chen
2002 Medical Imaging 2002: Physiology and Function from Multidimensional Images  
In this paper, we present a new electronic colon cleansing technology, which employs a hidden Markov random filed (MRF) model to integrate the neighborhood information for overcoming the non-uniformity  ...  The method utilizes a hidden MRF Gibbs model to integrate the spatial information into the Expectation Maximization (EM) model-fitting MAP algorithm.  ...  DISCUSSION AND CONCLUSIONS We have presented an electronic colon cleansing technology based on a hidden MRF model and MAP-EM algorithm for extracting the colon lumen from abdominal CT images.  ... 
doi:10.1117/12.463607 fatcat:7z2ok7vjsnbupcdwwwr47cavdq

Handwritten Tifinagh Text Recognition using Neural Networks and Hidden Markov Models

Badre-eddine ElKessab, Cherki Daoui, Belaid Bouikhalene
2013 International Journal of Computer Applications  
Here in this work a neural network (the multi-layer perceptron MLP) and Hidden Markov Models (HMM) are proposed for handwritten characters identification.  ...  This work has achieved approximately 80% of success rate for Tifinagh handwritten text identification. General Terms Hidden Markov Model HMM, Neural Network NN, Baum-Welch algorithm.  ...  HIDDEN MARKOV MODELS Hidden Markov models (HMMs), is a statistical model in which the system being modeled is assumed to be a Markov process with unknown parameters.  ... 
doi:10.5120/13354-0127 fatcat:74yoci27azeulfdyf6q5vkls2m


Vincey Jeba Malar.V .
2013 International Journal of Research in Engineering and Technology  
Focused on the solution to these problems, a Medical Diagnosis System based on Hidden Markov Model (HMM) is presented.  ...  Interpretation of Medical image is often difficult and time consuming, even for the experienced Physicians.  ...  For non-observable states, this leads to a Hidden Markov Model (HMM).  ... 
doi:10.15623/ijret.2013.0212014 fatcat:fchdyy5kpzh7dplnqu2i6r3wye

Region Based Hidden Markov Random Field Model For Brain Mr Image Segmentation

Terrence Chen, Thomas S. Huang
2007 Zenodo  
In this paper, we present the region based hidden Markov random field model (RBHMRF), which encodes the characteristics of different brain regions into a probabilistic framework for brain MR image segmentation  ...  The recently proposed TV+L1 model is used for region extraction.  ...  We encode this information into the segmentation framework and propose the region based hidden Markov random field model (RBHMRF).  ... 
doi:10.5281/zenodo.1063069 fatcat:atui7axl7nemfp2qwcc6w6kd3i

Deep Intelligent Prediction Network: A Novel Deep Learning Based Prediction Model on Spatiotemporal Characteristics and Location Based Services for Big Data Driven Intelligent Transportation System

In addition, markov model is embedded to discover the hidden features .The experimental results demonstrates that proposed approaches achieves better results against state of art approaches on the performance  ...  The proposed model employs deep learning architecture to predict potential road clusters for passengers.  ...  Feature Extraction It extracts the normal and hidden features from the markov cluster. Features are extracted mostly based on frequencies.  ... 
doi:10.35940/ijitee.k1503.0981119 fatcat:wnyxlv4pvfgfvbti2tcprzqfwu

Offline Signature Recognition using Hidden Markov Model (HMM)

S. Adebayo Daramola, T. Samuel Ibiyemi
2010 International Journal of Computer Applications  
This paper presents a recognition system for offline signatures using Discrete Cosine Transform (DCT) and Hidden Markov Model (HMM).  ...  Keywords Offline Signature, DCT Features, Hidden Markov Model.  ...  The technique is based on Discrete Cosine transform and Hidden Markov Model.  ... 
doi:10.5120/1454-1967 fatcat:vtfqyxwbm5fy7cipmpu4dlxnoi

Segment Model Based Vehicle Motion Analysis

Pengfei Zhu, Weiming Hu, Xi Li, Li Li
2009 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance  
In the experiments, we compare our approach with the template matching method based on the Hausdorff distance and the state space method based on the Hidden Markov Model (HMM).  ...  In this paper, we propose a framework for analyzing real vehicle motion in visual traffic surveillance by using Segment Model (SM), which is a kind of probabilistic model.  ...  In the experiments, we have compared our approach with the template matching method based on the Hausdorff distance and the state space method based on the Hidden Markov Model (HMM).  ... 
doi:10.1109/avss.2009.9 dblp:conf/avss/ZhuHLL09 fatcat:34jqyr2berecti3qdkyiidnjue

A Novel Assessment of Various Bio-Imaging Methods for Lung Tumor Detection and Treatment by using 4-D and 2-D CT Images

Antony Judice A, Dr K Parimala Geetha
2013 International Journal of Biomedical Science  
Focused on the solution to this problem, a Medical Diagnosis System based on Hidden Markov Model (HMM) is presented.  ...  Secondly separate the lung areas from an image by a segmentation process (by Thresholding and region growing techniques). Finally we developed HMM for the classification of Cancer Nodule.  ...  For observable state sequences (state is known from data), this leads to a Markov chain model .For non-observable states, this leads to a Hidden Markov Model (HMM).A hidden Markov model (HMM) is a statistical  ... 
pmid:23847454 pmcid:PMC3708268 fatcat:mffr6if4fzf6jnv63izdkb2de4
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