Search Results - (( sequence extraction method algorithm ) OR ( based classification using algorithm ))

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  1. 1
    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm

    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

    Published 2017
    “…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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  2. 2
    Classification and detection of intelligent house resident activities using multiagent

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
    “…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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  3. 3
    An efficient computational intelligence technique for classification of protein sequences

    An efficient computational intelligence technique for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Samir, B.B.

    Published 2014
    “…In this paper, a frequency-based feature encoding technique has been used in the proposed framework to represent amino acids of a protein's primary sequence. …”
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  4. 4
    Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification

    Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification by Dwi Swasono, Rachmad

    Published 2025
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  5. 5
    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
    “…The performance of this method can work in some specific use cases and effectively solving the problem of the inaccurate classification and detection of typical features.…”
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  6. 6
    Geometry based lip reading system using Multi Dimension Dynamic Time Warping

    Geometry based lip reading system using Multi Dimension Dynamic Time Warping by M. Z., Ibrahim, Mulvaney, D. J.

    Published 2012
    “…This paper describes an automatic lip reading system consisting of two main modules 1) a pre-processing module able to extract lip geometry information from the video sequence and 2) a classification module to identify the visual speech based on dynamic lip movements. …”
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  7. 7
    ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING

    ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING by MOHD RASHDAN, NURUL FARAH

    Published 2019
    “…In the frame process, important information will be extracted from the video images accordance to frame sequence where Spatial Temporal -Interest-Point (STIP) is used based on Harris’ Corner detection. …”
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  8. 8
    Convolutional neural networks with feature fusion method for automatic modulation classification

    Convolutional neural networks with feature fusion method for automatic modulation classification by Elshebani, Mohamed Salem, Ali, Yahya, Azroug, Nser, Khalifa, Ramdan A. M., Khalifa, Othman Omran, Saeed, Rashid A.

    Published 2023
    “…However, most existing modulation classification algorithms are neglecting the fact of mixing features between different representations, and the importance of features fusion method. …”
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  9. 9
    Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf

    Prediction Of Antimicrobial Peptides Based On Sequence Alignment And Secondary Structure Sequence And Segment Sequence.pdf by Soh , Meng Wah

    Published 2015
    “…Thus, a computational tool with more effective and accurately predicting novel AMPs is highly demanded to provide more candidates and useful insights for drug design. In this study, a new algorithm is proposed as a computational tool by integrating the sequence alignment method and the secondary structure sequence (SSS) and segment sequence (SS). …”
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  10. 10
    Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer

    Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer by Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha

    Published 2016
    “…In this paper, we employed three marker selection algorithms to select relevant miRNAs that are directly responsible for cancer classification. …”
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  11. 11
    Detection and Classification of Moving Objects for an Automated Surveillance System

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  12. 12
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  13. 13
    Detection and classification of moving objects for an automated surveillance system

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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  14. 14
    A study on component-based technology for development of complex bioinformatics software

    A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

    Published 2004
    “…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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  15. 15
    A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer

    A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

    Published 2023
    “…Sentiment analysis algorithms used to classify the sentiment of tweets on social media platforms such as Twitter face challenges when dealing with idiomatic expressions and figurative language used by users. …”
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  16. 16
    A comparative study of supervised machine learning approaches for slope failure production

    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”
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  17. 17
    SOMEA: self-organizing map based extraction algorithm for DNA motif identification with heterogeneous model

    SOMEA: self-organizing map based extraction algorithm for DNA motif identification with heterogeneous model by Lee, Nung Kion, Wang, Dianhui

    Published 2011
    “…This assumption has some limitations because both sequence signals have distinct properties. Results: This paper aims to develop a Self-Organizing Map (SOM) based clustering algorithm for extracting binding sites in DNA sequences. …”
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  18. 18
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
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  19. 19
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  20. 20
    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking

    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

    Published 2012
    “…This problem is addressed by proposing an accurate and robust centerline extraction method. Starting at each detected seed point, the centerline extraction method utilizes eigenvalues and eigenvectors of Hessian matrix for the pixels located on a semi-circular scanning profile for robust estimation of the next centerline point. …”
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