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  1. 1
    Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan

    Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan by Hasan, Haitham Sabah

    Published 2014
    “…The results show that hand contour method has a performance of 71.30% recognition, while complex moments has a better performance of 86.90% recognition rate.…”
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  2. 2
    Old Jawi manuscript: Digital recognition / Zaidi Razak

    Old Jawi manuscript: Digital recognition / Zaidi Razak by Zaidi, Razak

    Published 2016
    “…The literature review in this research looks at works conducted in the past on line and character segmentation as well as recognition systems. The information gathered is useful for the development of a line segmentation algorithm, a new character segmentation algorithm, as well as a recognition algorithm which is based on the use of a unique code and Hamming distance calculation. …”
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  3. 3
    Handwritten digits recognition based on improved label propagation algorith

    Handwritten digits recognition based on improved label propagation algorith by Jie, M., Aziz, I.A., Hasbullah, H., Azizan, S.A.B.

    Published 2016
    “…Handwritten digits recognition is a practical problem in pattern recognition applications, is of academic and commercial interest. …”
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    Conference or Workshop Item
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  4. 4
    Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman

    Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman by Seman, Noraini

    Published 2012
    “…However, traditional ANNs have many fundamental problems regarding a long and uncertain training process, which in most cases learning or training of a neural network is based on a trial and error method. …”
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  5. 5
    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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  6. 6
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  7. 7
    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
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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  8. 8
    Face recognition using integrated discrete cosine transform and kernel fisher discriminant analysis

    Face recognition using integrated discrete cosine transform and kernel fisher discriminant analysis by Janahiraman T.V., Omar J., Farukh H.N.

    Published 2023
    “…This situation is often referred as "small sample size" (SSS) problem. Moreover, FLD is a linear algorithm by nature. …”
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  9. 9
    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 a real world, pattern recognition problems in diversified forms are ubiquitous and are critical in most human decision making tasks. …”
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  10. 10
    Image recognition using Artificial Immune systems approach

    Image recognition using Artificial Immune systems approach by Hasnah, Ahmad, Puteh, Saad

    Published 2009
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  11. 11
    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System

    Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

    Published 2011
    “…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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  12. 12
    A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm

    A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm by Tahereh Hassanzadeh, Karim Faez, Golnaz Seyfi

    Published 2012
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  13. 13
    Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm

    Quranic diacritic and character segmentation and recognition using flood fill and k-nearest neighbors algorithm by Alotaibi, Faiz E A L

    Published 2019
    “…The detection, recognition and conversion of the characters in an image into a text are called optical character recognition (OCR). …”
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  14. 14
    Character classification for license plate recognition system based on image processing using MATLAB

    Character classification for license plate recognition system based on image processing using MATLAB by Hashim, Mustafa Adil

    Published 2016
    “…A License Plate Recognition System (LPRS) is one of the most important systems used for monitoring and controlling transportation and traffic in many countries. …”
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  15. 15
    Modem Recognition Algorithm for Software Defined Radio Base Station

    Modem Recognition Algorithm for Software Defined Radio Base Station by Rukumangatha Rajah, Sivaraman

    Published 2004
    “…The average latency for each QPSK, MSK, QASK, and BPSK modulation scheme is approximately 20ms. As a whole, the proposed modem recognition algorithm demonstrated successful recognition of QPSK, MSK, QASK, and BPSK for a lower-bound channel SNR greater than 5dB with average processing time of approximately 75ms. …”
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  16. 16
    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition

    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition by Mahmood, Saif F., Marhaban, Mohammad Hamiruce, Rokhani, Fakhrul Zaman, Samsudin, Khairulmizam, Arigbabu, Olasimbo Ayodeji

    Published 2017
    “…The proposed FASTA-ELM algorithm is evaluated on face gender recognition problem using 5 benchmarked datasets. …”
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  17. 17
    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim

    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

    Published 2018
    “…Face recognition involves the comparison of a given face with other faces in a database. …”
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  18. 18
    Shape matching and object recognition using dissimilarity measures with Hungarian algorithm

    Shape matching and object recognition using dissimilarity measures with Hungarian algorithm by Chitra, D., Manigandan, T., Devarajan, N.

    Published 2009
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  19. 19
    The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition

    The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition by Othman, Mahmod, Syed Abdullah, Sharifah Lailee, Ahmad, Khairul Adilah, Abu Bakar, Mohd Nazari, Mansor, Ab Razak

    Published 2016
    “…To address this problem, this paper proposes a fusion of selected edge detection algorithms with mathematical morphology to enhance the ability to detect the object shape boundary. …”
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  20. 20
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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