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  1. 1
    Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network

    Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

    Published 2019
    “…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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  2. 2
    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman

    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

    Published 2017
    “…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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  3. 3
    Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation

    Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

    Published 2019
    “…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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  4. 4
    A Novel Aggregate Classification Technique Using Moment Invariants and Cascaded Multilayered Perceptron Network

    A Novel Aggregate Classification Technique Using Moment Invariants and Cascaded Multilayered Perceptron Network by Md Sani, Zamani

    Published 2009
    “…This article discusses a novel method for automatic classification of aggregate shapes using moment invariants and artificial neural networks. …”
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  5. 5
    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
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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  6. 6
    Automated plant classification system using a hybrid of shape and color features of the leaf

    Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

    Published 2016
    “…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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  7. 7
    Detection of acute leukaemia cells using variety of features and neural networks

    Detection of acute leukaemia cells using variety of features and neural networks by A. S., Abdul Nasir, Mohd Yusoff, Mashor, Prof. Dr., H., Rosline

    Published 2011
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  8. 8
    Biologically inspired mobile agent-based sensor network (BIMAS)

    Biologically inspired mobile agent-based sensor network (BIMAS) by Ponnusamy, V., Low, T.J., Amin, A.H.M.

    Published 2014
    “…Simulation was conducted to evaluate the proposed mechanism and a prototype was developed to show the feasibility of mobile agent de-ployment and energy provisioning. …”
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  9. 9
    Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian

    Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian by Saffian, Norhafizah

    Published 2017
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  10. 10
    Automated leaf alignment and partial shape feature extraction for plant leaf classification

    Automated leaf alignment and partial shape feature extraction for plant leaf classification by Hamid, Laith Emad, Syed Mohamed, Syed Abdul Rahman Al-Haddad

    Published 2019
    “…The experimental results indicate the ability of the proposed alignment algorithm to align leaves with different shapes and maintain a correct classification accuracy regardless of the orientation of the input leaf samples. …”
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  11. 11
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover with simple concatenating features, classification results are not optimal. It is crucial to integrate these heterogeneous features to create more accurate and robust classification results than using each individual type of features. …”
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  12. 12
    Behavioural features for mushroom classification

    Behavioural features for mushroom classification by Ismail, Shuhaida, Zainal, Amy Rosshaida, Mustapha, Aida

    Published 2018
    “…The Principal Component Analysis (PCA) algorithm is used for selecting the best features for the classification experiment using Decision Tree (DT) algorithm. …”
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  13. 13
    Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib

    Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib by Ab Jabal, Mohamad Faizal, Hamid, Suhardi, Shuib, Salehuddin

    Published 2013
    “…As a result Wu et al. [1] was successful developed an efficient algorithm for the plant classification. 32 kinds of plants have been classified by using the algorithm. …”
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  14. 14
    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah

    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

    Published 2012
    “…The results indicated that MLP is sufficient, and optimal enough to be used for classification of the selected freshwater algae. …”
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  15. 15
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. …”
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  16. 16
    Classification of Citrus (Rutaceae) by Using Image Processing

    Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

    Published 2019
    “…The study present how to classify selected Citrus genus species with similar leaf shapes based on leaf images by using digital image vision machine classification. …”
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    Undergraduate Final Project Report
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  17. 17
    Application Of Neural Network In Malaria Parasites Classification

    Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

    Published 2006
    “…Hybrid Multilayer Perceptron (HMLP) network with modified recursive prediction error algorithm will be developed using Borland C++ Builder. …”
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  18. 18
    Region-growing based segmentation and bag of features classification for breast ultrasound images

    Region-growing based segmentation and bag of features classification for breast ultrasound images by Lee, Lay Khoon

    Published 2017
    “…In the next stage, which is the segmentation stage, region growing algorithm is used to automatically detect tumors in ultrasound images. …”
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  19. 19
    An image-based children age range verification and classification based on facial features angle distribution and face shape elliptical ratio

    An image-based children age range verification and classification based on facial features angle distribution and face shape elliptical ratio by Razalli, Husniza, Rahmat, Rahmita Wirza O. K, Khalid, Fatimah, Sulaiman, Puteri Suhaiza

    Published 2017
    “…The method was tested on FG-NET aging database. The classification of children from adults and the verification of children age range are implemented using SVM and Multi-SVM classification process. …”
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  20. 20
    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules

    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
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