Search Results - (( data verification method algorithm ) OR ( data classifications using algorithm ))

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  1. 1
    Non-fiducial based electrocardiogram biometrics with kernel methods

    Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

    Published 2017
    “…At classification level, Gaussian multi-class Support Vector Machine (SVM) with the One-Against-All (OAA) approach is proposed to evaluate verification performance rates of the feature extraction algorithms. …”
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  2. 2
    Non-fiducial based ECG biometric authentication using one-class support vector machine

    Non-fiducial based ECG biometric authentication using one-class support vector machine by Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

    Published 2017
    “…The experimental results show that Kernel Principal Component Analysis has lower error rate in binary and one-class SVMs on random unknown ECG data sets. Moreover, one-class SVM can be robust recognition algorithm for ECG biometric verification if the sufficient number of biometric samples is available.…”
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  3. 3
    A novel architecture to verify offline hand-written signatures using convolutional neural network

    A novel architecture to verify offline hand-written signatures using convolutional neural network by Alkaabi S., Yussof S., Almulla S., Al-Khateeb H., Alabdulsalam A.A.

    Published 2023
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  4. 4
    An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder

    An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder by Chen, Ruo Han, Ng, Boon Sim, Paramasivam, Shamala, Ren, Li

    Published 2024
    “…The experimental results show that the overall accuracy of BSETG algorithm is maintained between 70% and 90%, the response speed of BSETG algorithm is relatively fast, and the success rate of BSETG algorithm is relatively stable to a large extent.…”
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  5. 5
    Fingerprint feature extraction based discrete cosine transformation (DCT)

    Fingerprint feature extraction based discrete cosine transformation (DCT) by Chin Kim On, Paulraj M. Pandiyan, Sazali Yaacob, Azali Saudi

    Published 2009
    “…The extracted nCT data is used as input for the backpropagation neural network training for personal identification.…”
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  6. 6
    Human Spontaneous Emotion Detection System

    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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  7. 7
    Secure Access To Authorized Resources Based On Fingerprint Authentication

    Secure Access To Authorized Resources Based On Fingerprint Authentication by Elmadani, Ahmed Baba

    Published 2003
    “…The A VL tree is used to increase the compression ratio as its compression algorithm works efficiently for all types of data. …”
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  8. 8
    Multi-stage feature selection in identifying potential biomarkers for cancer classification

    Multi-stage feature selection in identifying potential biomarkers for cancer classification by Wong, Yit Khee, Chan, Weng Howe, Nies, Hui Wen, Moorthy, Kohbalan

    Published 2022
    “…Therefore, this study aims to investigate and develop a better feature selection to identify potential biomarkers from gene expression data and construct a deep neural network classification model using these selected features. …”
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  9. 9
    Stroke-to-stroke matching in on-line signature verification

    Stroke-to-stroke matching in on-line signature verification by Ahmad Jaini, Azhar

    Published 2010
    “…On-line Signature Verification is a field of verifying the time series signature data that normally obtained from the tablet-based device. …”
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  10. 10
    Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi

    Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi by Muhammad, Faisal

    Published 2024
    “…Using the cosine similarity algorithm for knowledge recommendation is village identified, utilizing community feedback as the foundation. …”
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  11. 11
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  12. 12
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  13. 13
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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  14. 14
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  15. 15
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  16. 16
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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  17. 17
    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
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  18. 18
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  19. 19
    Development of classification algorithms of human gait

    Development of classification algorithms of human gait by Koh, Chee Hong

    Published 2022
    “…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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  20. 20
    Text Extraction Algorithm for Web Text Classification

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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