Search Results - (( tissues classification using algorithm ) OR ( pattern classification methods algorithm ))

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  1. 1
    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm

    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

    Published 2015
    “…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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  2. 2
    HEP-2 CELL FEATURE EXTRACTION USING WAVELET AND INDEPENDENT COMPONENT ANALYSIS

    HEP-2 CELL FEATURE EXTRACTION USING WAVELET AND INDEPENDENT COMPONENT ANALYSIS by NUR THANIA AWATIF BINTI MOHAMAD ROSDI, NUR THANIA AWATIF BINTI MOHAMAD ROSDI

    Published 2013
    “…Then Support Vector Machine (SVM) is used to perform the classifications parts using the features extracted from both methods. …”
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  3. 3
    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…This is followed by the clustering of the liver tissues using particle swarm optimized spatial FCM algorithm. …”
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  4. 4
    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES

    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES by MD HASIM, SITI MASTURA

    Published 2013
    “…Next, to design an algorithm that can automatically identify the 2 patterns of the HEp-2 cell tested using ANA. …”
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  5. 5
    “SEGMENTATION OF ANTI NEUTROPHIL CYTOPLASMIC ANTIBODIES (ANCA) IMAGES BASED ON WATERSHED AND WAVELET”

    “SEGMENTATION OF ANTI NEUTROPHIL CYTOPLASMIC ANTIBODIES (ANCA) IMAGES BASED ON WATERSHED AND WAVELET” by Nasir Nasir, Muhamad Hasyeme

    Published 2013
    “…Using Rand Index method, the result of segmentations is verified. …”
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  6. 6
    A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data

    A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data by Yeo, Lee Chin, Deris, Safaai

    Published 2005
    “…Gene Selection Plays An Important Role Prior To Tissue Classification. In This Paper, A Study On Numerous Combinations Of Gene Selection Techniques And Classification Algorithms For Classification Of Microarray Gene Expression Data Is Presented. …”
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  7. 7
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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  8. 8
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are a lot of feature extraction methods and classification methods for iris classification. …”
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  9. 9
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  10. 10
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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  11. 11
    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition

    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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  12. 12
    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter

    Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter by Tengku Azis, Tengku Mohd Syamim

    Published 2015
    “…In the classification stage, the k-NN classifier is used to classify the CT images to two different classes which are Normal Tissue (NT) and Abnormal Tissue; Centrilobular Emphysema (CLE) and Paraseptal Emphysema (PSE). …”
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  13. 13
    Effective gene selection techniques for classification of gene expression data

    Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

    Published 2005
    “…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. …”
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  14. 14
    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
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  15. 15
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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  16. 16
    Grid base classifier in comparison to nonparametric methods in multiclass classification

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. …”
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  17. 17
    Design of a pattern classification system using extreme learning machine

    Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

    Published 2024
    text::Final Year Project
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  18. 18
    Multilevel learning in Kohonen SOM network for classification problems

    Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

    Published 2006
    “…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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  19. 19
    Design of a pattern classification system using extreme learning machine

    Design of a pattern classification system using extreme learning machine by Sakthivel Thangavelu

    Published 2023
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  20. 20
    Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns

    Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns by Lei, I. L., Teh, Phoey Lee *, Si, Yain-Whar

    Published 2021
    “…To identify chart patterns, time series data is usually segmented before it can be processed by different classification methods. …”
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