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  1. 1
    AUTOMATED VEHICLE COUNTING AND CLASSIFICATION SYSTEM FOR TRAFFIC CENSUS

    AUTOMATED VEHICLE COUNTING AND CLASSIFICATION SYSTEM FOR TRAFFIC CENSUS by MOHMOOD NOR, MOHD NAZIF HAWARI

    Published 2012
    “…Computer vision technology is used to achieve this objective. For the vehicle detection, background subtraction and approximate median algorithm are used. …”
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  2. 2
    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
    “…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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  3. 3
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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  4. 4
    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 diacritic detections are performed using a region-based algorithm with 89% accuracy and 95% improved by using flood fill segmentations method. 2DMED feature extraction accuracy was 90% for diacritics and 96% improved by applied CNN. …”
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  5. 5
    A comparative study in classification techniques for unsupervised record linkage model

    A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

    Published 2011
    “…In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. …”
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  6. 6
    Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram

    Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram by Abd Rahman, Faridah, Othman, Mohd Fauzi, Hamzah, Mohd Ilham Rusydan Hamzah

    Published 2018
    “…To overcome this problem, an algorithm to automatically detect and remove the artifacts from EEG signals is highly desirable. …”
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  7. 7
    CORROSION DAMAGE ANALYSIS USING IMAGE PROCESSING

    CORROSION DAMAGE ANALYSIS USING IMAGE PROCESSING by DEMPI, CHRISTIE BANGI

    Published 2018
    “…NDE is an automatic detection method for corrosion classification which can be implemented for the inspection of the pipelines and storage tanks in the oil and gas industry as it will not disturb their properties and performance.…”
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  8. 8
    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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  9. 9
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The RSNN provides a novel methodology for designing nonlinear filters without prior knowledge of the problem domain. The RNN was used to detect patterns present in satellite image. …”
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  10. 10
    Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.]

    Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.] by Kasim, Nadia, Zainol Abidin, Siti Nazifah, Abu Mangshor, Nur Nabilah, Mohamed Hamzah, Hazwa Hanim, Abd Rahim, Nurul Zahirah

    Published 2019
    “…Lack of knowledge and skill of maintaining fruit quality standard to match the international standard is a problem faced by the farmers. This study attempted to propose a system that uses image processing to detect the maturity stage of banana based on its color and size using Support Vector Machine (SVM) learning algorithm. …”
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  11. 11
    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve higher accuracy in fall detection system

    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

    Published 2022
    “…In these approaches, machine learning techniques have been conducted to provide automatic classification and to improve accuracy. One of the most commonly used algorithms is Support Vector Machine (SVM). …”
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  12. 12
    Advances in automatic insect classification

    Advances in automatic insect classification by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). …”
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  13. 13
    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System

    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System by Khosropanah, Pegah

    Published 2011
    “…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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  14. 14
    Adaptive background modeling for dynamics background

    Adaptive background modeling for dynamics background by Zainuddin, Nor Afiqah, Mohd Mustafah, Yasir, Shafie, Amir Akramin, Azman, Amelia Wong, Rashidan, Mohd. Ariff, A. Aziz, Nor Nadirah

    Published 2016
    “…Contrast adjusting method is used to reduce the problem of incorrectly classified foreground which is shadow problem. …”
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  15. 15
    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…Wearable devices, smart-phones and ambient environments devices are equipped with variety of sensors such as accelerometers, gyroscopes, magnetometer, heart rate, pressure and wearable camera for activity detection and monitoring. These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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  16. 16
    A systematic review of deep learning microalgae classification and detection

    A systematic review of deep learning microalgae classification and detection by Madkour, Dina M., Mohd Ibrahim, Shapiai, Shaza Eva, Mohamad, Aly, Hesham Hamdy, Zool Hilmi, Ismail, Mohd Zamri, Ibrahim

    Published 2023
    “…A systematic literature review or SLR has been conducted to determine how deep learning and machine learning have improved and enhanced automatic microalgae classification rather than manual classification. 51 articles have been included from well-known databases. …”
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  17. 17
    Feature selection and classification of ulcerated lesions using statistical analysis for WCE images

    Feature selection and classification of ulcerated lesions using statistical analysis for WCE images by Suman, S., Hussin, F.A., Malik, A.S., Ho, S.H., Hilmi, I., Leow, A.H.-R., Goh, K.-L.

    Published 2017
    “…The chosen feature vector was used to compute the performance metrics using SVM with grid search method for maximum efficiency. …”
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  18. 18
    Vision based entomology: a survey

    Vision based entomology: a survey by Hassan, Siti Noorul Asiah, Abdul Rahman, Nur Nadiah Syakira, Htike@Muhammad Yusof, Zaw Zaw, Shoon , Lei Win

    Published 2014
    “…This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). …”
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  19. 19
    A multi-filter feature selection in detecting distributed denial-of-service attack

    A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

    Published 2019
    “…It consists of 3-stage procedures: feature ranking, feature selection and classification. Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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  20. 20
    Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model

    Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model by Afsoon Badiei, Saeed Meshgini, Ali Farzamnia

    Published 2020
    “…The notion is very effective in the detection of sleep disorders. In this paper, the detection of arousal events is performed using an automatic analysis of EEG and ECG signals. …”
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