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  1. 1
    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
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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  2. 2
    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 two approaches were applied to image pattern recognition problems. The RSNN was applied to automatic target recognition problem. …”
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  3. 3
    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
    “…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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  4. 4
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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  5. 5
    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
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  6. 6
    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah

    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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  7. 7
    Deep plant: A deep learning approach for plant classification / Lee Sue Han

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…The existing CNN based approaches can only capture the similar region-wise patterns within an image but not the structural patterns of a plant composed of varying number of plant views images composed of one or more organs. …”
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  8. 8
    Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issues, and knowledge gaps in fundus medical images

    Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issue... by Abdulsahib A.A., Mahmoud M.A., Mohammed M.A., Rasheed H.H., Mostafa S.A., Maashi M.S.

    Published 2023
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  9. 9
    Underwater Image Recognition using Machine Learning

    Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

    Published 2024
    “…It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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  10. 10
    2D and 3D video scene text classification

    2D and 3D video scene text classification by Xu, J., Shivakumara, P., Lu, T., Tan, C.L.

    Published 2014
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  11. 11
    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES

    FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES by MD HASIM, SITI MASTURA

    Published 2013
    “…Next, to design an algorithm that can automatically identify the 2 patterns of the HEp-2 cell tested using ANA. …”
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  12. 12
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. …”
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  13. 13
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. …”
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  14. 14
    Spiking Neural Network For Energy Efficient Learning And Recognition

    Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

    Published 2020
    “…The use of applications consumes energy and hard to perform through standard programmed algorithms. Spiking neural networks have emerged that achieve favourable advantages in terms of energy and time efficiency by using spikes for computation and communication as well as solving different problems such as pattern classification and image processing. …”
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  15. 15
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. …”
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  16. 16
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Audrey Huong, Kim Gaik Tay, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. …”
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  17. 17
    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods

    Dorsal Hand Vein Pattern Recognition: A Comparison between Manual and Automatic Segmentation Methods by Waheed Ali Laghari, Waheed Ali Laghari, Audrey Huong, Kim Gaik Tay, Audrey Huong, Kim Gaik Tay, Chang Choon Chew, Chang Choon Chew

    Published 2023
    “…The HHM combined histogram equalization and morphological and thresholding-based algorithms to localize veins from hand images. …”
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  18. 18
    Extrema Points Application In Determining Iris Region Of Interest

    Extrema Points Application In Determining Iris Region Of Interest by Othman, Zuraini, Kasmin, Fauziah, Syed Ahmad, Sharifah Sakinah, Abdullah, Azizi

    Published 2019
    “…Hence, to address this issue, this paper proposed a method of iris localisation in the case of ideal and non-ideal iris images. In this study, the algorithm was based on finding the classification for the region of interest (ROI) with the help of a Support Vector Machine (SVM) by applying a histogram of grey level values as a descriptor in each region from the region growing technique. …”
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  19. 19
    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 pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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  20. 20
    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
    “…The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods.…”
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