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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    Development of sorting system for oil palm in vitro shoots using machine vision approach

    Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

    Published 2014
    “…Region-based features, namely area, centroid, aspect ratio, extent and two cropping points have been represented in the shape of OPTC in vitro shoots. By using k-means algorithm the extracted features have been evaluated. …”
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  6. 6
    Supervised neural network classifier for voice pathology

    Supervised neural network classifier for voice pathology by Murugesa Pandiyan, Paulraj, Prof. Madya Dr, Sazali, Yaacob, Prof. Dr., Sivanandam, S. N., Hariharan, Muthusamy

    Published 2011
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  7. 7
    Fuzzy voice classifier and fuzzy voice pathology identification system

    Fuzzy voice classifier and fuzzy voice pathology identification system by Sathees Kumar, Nataraj, Sazali, Yaacob, Prof. Dr., Ahamad Nazri, Abdullah

    Published 2012
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  8. 8
    Multilanguage speech-based gender classification using time-frequency features and SVM classifier

    Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

    Published 2021
    “…Various techniques like framing, Fast Fourier Transform (FFT), auto-correlation, filtering, power calculations, speech frequency analysis, and feature extraction and formation are applied on speech samples. …”
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  9. 9
    Structural steel plate damage detection using DFT spectral energy and artificial neural network

    Structural steel plate damage detection using DFT spectral energy and artificial neural network by Paulraj, Murugesa Pandiyan, Prof. Madya Dr., Mohd Shukri, Abdul Majid, Sazali, Yaacob, Prof. Dr., Abdul Hamid, Adom, Prof. Madya Dr., Krishnan, Pranesh R.

    Published 2011
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  10. 10
    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization

    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization by Mizher, Manar Abduljabbar Ahmad, Ang, Mei Choo, Sheikh Abdullah, Siti Norul Huda, Kok, Weng Ng

    Published 2019
    “…The objective of this work is to improve our previous action key frames extraction algorithm (AKF) by adapting a threshold which selects action key frames as final key frames. …”
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  11. 11
    Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials

    Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials by Ng, Sok Choo

    Published 2013
    “…(iii) The image ofthe defect region is reconstructed by using the attenuation of the reflected ultrasound signal (iv) Entropy-based fuzzy k-nearest neighbour classification method is used to extract the feature of the defects. …”
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  12. 12
    An improved method in speech signal input representation based on DTW technique for NN speech recognition system

    An improved method in speech signal input representation based on DTW technique for NN speech recognition system by Sudirman, Rubita, Salleh, Sh. Hussain, Salleh, Shaharuddin

    Published 2007
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  13. 13
    A fast feature extraction algorithm for image and video processing

    A fast feature extraction algorithm for image and video processing by Abdulhussain, Sadiq H., Ramli, Abdul Rahman, Mahmmod, Basheera M., Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Baker, Thar, Flayyih, Wameedh Nazar, Jassim, Wissam A.

    Published 2019
    “…These features are used to represent the local visual content of images and video frames. We compared the proposed method with the traditional approach of feature extraction using a standard image technique. …”
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  14. 14
    AR oriented pose matching mechanism from motion capture data

    AR oriented pose matching mechanism from motion capture data by Iqbal J., Sidhu M.S., Ariff M.B.M.

    Published 2023
    “…In order to extract the exact matched pose, the frame sequence is divided into pose feature frame and skeletal data frame by the use of pose matching dance training movement recognition algorithm (PMDTMR). …”
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  15. 15
    Automated threshold detection for object segmentation in colour image

    Automated threshold detection for object segmentation in colour image by Akhtaruzzaman, Md., Shafie, Amir Akramin, Khan, Md. Raisuddin

    Published 2016
    “…In solving this issue, this paper presents an Automated Threshold Detection Algorithm, H(•). The algorithm is applied in segmenting human lower limbs from a series of image frames of human walking. …”
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  16. 16
    Local DTW coefficients and pitch feature for back-propagation NN digits recognition

    Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

    Published 2006
    “…The LPC features vectors are aligned between the source frames to the template using our DTW frame fixing (DTW-FF) algorithm. …”
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  17. 17
    Time normalization of LPC feature using warping method

    Time normalization of LPC feature using warping method by Sudirman, Rubita, Salleh, Sh. Hussain, Khalid, Puspa Inayat, Ahmad, Abd. Hamid

    Published 2005
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  18. 18
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This method is capable to shorten the process time of the computation-intensive program in this research to process the live images frame by frame, which received from a laptop webcam to achieve real-time video processing. …”
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  19. 19
    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition

    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…The LPC features vectors are aligned between the source frames to the template using our DTW frame fixing (DTW-FF) algorithm. …”
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  20. 20
    Dengue classification system using clonal selection algorithm / Karimah Mohd

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

    Published 2012
    “…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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