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  1. 1
    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
    “…After that, next stage, which is the classification stage, bag of feature (BoF). After segmentation done, the classification will take place when ultrasound is input. …”
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  2. 2
    Pattern Classification of Human Epithelial Images

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…First of all, image enhancement will take part in order to boost efficiency of algorithm by implementing some of the adjustment and filtering technique to increase the visibility of image. …”
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  3. 3
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  4. 4
    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning

    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

    Published 2023
    “…Using the proposed model, an experiment was conducted on the Fashion-MNIST dataset, taking 6,000 images as the training dataset and 1,000 images as the testing dataset. …”
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  5. 5
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  6. 6
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  7. 7
    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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  8. 8
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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  9. 9
    Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network

    Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

    Published 2021
    “…However, conventional bottom-up saliency map algorithms regularly failed to localize salient or pathological anomalies in medical images. …”
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  10. 10
    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation

    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…However, the standard FCM algorithm takes a long time to partition a large dataset. …”
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  11. 11
    Comparison between pixel-based and object based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia

    Comparison between pixel-based and object based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Mohd Shafri, Helmi Zulhaidi, Sulaiman, Md. Nasir, Husin, Nor Azura

    Published 2015
    “…This study focuses on the comparison between pixel-based classification and object-based classification of five machine learning algorithms including Parallelepiped (PP), Minimum Distance (MD), Maximum Likelihood (ML), Mahalanobis Distance (MH) and Neural Network (NN) using radar satellite image in extracting that flood extent. …”
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  12. 12
    Comparison between pixel-based and object-based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia

    Comparison between pixel-based and object-based classifications using radar satellite image in extracting massive flood extent at northern region of Peninsular Malaysia by Abd Manaf, Syaifulnizam, Mustapha, Norwati, Mohd Shafri, Helmi Zulhaidi, Sulaiman, Md Nasir, Husin, Nor Azura

    Published 2015
    “…Year 2010 massive flood hit the northern region of Peninsular Malaysia particularly Perlis and Kedah involved several districts and destroyed many agricultural areas and the infrastructure.This study focuses on the comparison between pixel-based classification and object-based classification of five machine learning algorithms including Parallelepiped (PP), Minimum Distance (MD), Maximum Likelihood (ML), Mahalanobis Distance (MH) and Neural Network (NN) using radar satellite image in extracting that flood extent. …”
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  13. 13
    Support vector classification of remote sensing images using improved spectral Kernels

    Support vector classification of remote sensing images using improved spectral Kernels by Md. Sap, Mohd. Noor, Kohram, Mojtaba

    Published 2008
    “…In the case of hyper-spectral imagery the amount of information available prior to classification is a vast amount. Current available kernels do not take full advantage of the amount of information available in these images. …”
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  14. 14
    Decision tree as knowledge management tool in image classification

    Decision tree as knowledge management tool in image classification by Kusrini, , Harjoko, Agus

    Published 2008
    “…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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  15. 15
    A Real time specific weed discrimination system using multi-Level wavelet decomposition

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The test and analysis show that 97.26% classification accuracy over 350 sample images (broad & narrow) with 175 samples from each category of weeds and the proposed algorithm takes 29 ms as average time for the classification of the specific weeds.…”
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  16. 16
    A Real time specific weed discrimination system using multi-Level wavelet decomposition

    A Real time specific weed discrimination system using multi-Level wavelet decomposition by Siddiqi, M.H., Sulaiman, S., Faye, Ibrahima, Ahmad, I.

    Published 2009
    “…The test and analysis show that 97.26% classification accuracy over 350 sample images (broad & narrow) with 175 samples from each category of weeds and the proposed algorithm takes 29 ms as average time for the classification of the specific weeds.…”
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  17. 17
    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic

    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

    Published 2014
    “…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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  18. 18
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  19. 19
    BONE AGE ANALYSIS FROM BONE X-RAY

    BONE AGE ANALYSIS FROM BONE X-RAY by ABD GHANI, NOOR SYAZANA

    Published 2018
    “…To achieve the objectives, the bone age classification method will involve image segmentation of the x-ray, feature extraction from the segmented images and lastly, classification of bone age level. …”
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  20. 20
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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