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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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    Proceeding Paper
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  4. 4
    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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    Working Paper
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  5. 5
    Danger theory inspired artificial immune system for pattern recognition

    Danger theory inspired artificial immune system for pattern recognition by Chung Seng Kheau, Rayner Alfred, Lau, Hui Keng, Jason Teo, Mohd. Hanafi Ahmad Hijazi, Nurul'alam Mohd. Yaakub

    Published 2007
    “…Negative Selection (NS) algorithm is the most commonly researched algorithm within the AIS framework. …”
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    Research Report
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  6. 6
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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  7. 7
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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  8. 8
    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    “…A framework user is allowed to select from a list of features provided by the framework that he or she is interested in learning, and the system will give an example of application related to the selected features. …”
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  9. 9
    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification

    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. …”
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  10. 10
    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

    Published 2023
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  11. 11
    Sheet C1 Pattern Number Recognition Using Artificial Immune System Optimization

    Sheet C1 Pattern Number Recognition Using Artificial Immune System Optimization by Yuniarti Denita, Sari, Tri Basuki, Kurniawan, Edi Surya, Negara, Tata, Sutabri

    Published 2022
    “…In order to recognize the numerical patterns on sheet C1, we, therefore, require a method that uses the Artificial Immune System (AIS), specifically the CSA (Clonal Selection Algorithm) algorithm, which is one of the AIS system's algorithms for optimization. …”
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  12. 12
    Text searching algorithm using boyer moore horspool (BMH) algorithm

    Text searching algorithm using boyer moore horspool (BMH) algorithm by Siti Nurafiqah, Jaafar

    Published 2015
    “…We study about the selected technique which is Boyer Moore Horspool algorithm that used for searching the occurrences of a pattern (keyword) in a random text in medical database. …”
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    Undergraduates Project Papers
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  13. 13
    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim

    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

    Published 2006
    “…Based on this idea, the objective of this project is to develop an automated pattern recognition system based on neural network to recognize the pattern of loaded data file. …”
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    Research Reports
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  14. 14
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…Self data are regarded as the normal behavioral pattern of the monitored system. In this research, the Real-Valued Negative Selection with fixed-sized detectors (RNSA) and Real-Valued Negative Selection with variable-sized detectors (V-Detector) were applied for classification and detection of anomalies. …”
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  15. 15
    Lexicon-based and immune system based learning methods in Twitter sentiment analysis

    Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

    Published 2016
    “…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
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  16. 16
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
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  17. 17
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
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  18. 18
    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin

    Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

    Published 2017
    “…Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. …”
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  19. 19
    3D OBJECT ACQUISITION SYSTEM

    3D OBJECT ACQUISITION SYSTEM by RAMLEE, MUHAMMAD RAHISHAN

    Published 2014
    “…Pattern which give clear and vivid image when capture by the camera will be selected. …”
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    Final Year Project
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  20. 20
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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