Search Results - (( model evaluation means algorithm ) OR ( image classification using algorithm ))*

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  1. 1

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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    Thesis
  2. 2

    Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

    Published 2023
    “…The utility of deep convolutional neural network (DCNN) for sex and age estimation was evaluated using images generated from reconstructed 3- dimensional computed tomography images. …”
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    Thesis
  3. 3

    Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch by Fadilah, Norasyikin

    Published 2015
    “…The images are collected and analyzed using digital image processing techniques. k-means clustering algorithm is used to segment the image into two separate regions which are fruit and spike regions. …”
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  4. 4

    Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran by Amran, Aiman Syafwan

    Published 2023
    “…The object detection and classification algorithm achieved 91.9% mean average precision in metric evaluation. …”
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  5. 5

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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  6. 6

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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    Article
  7. 7

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training time, and their performance is compromised due to a higher misclassification rate. …”
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    Automated Vehicle Classification (AVC) using machine learning implementation in Malaysia's toll system by Hassan, Raini, Mohd Ridzal, Aisyah Afiqah, Fadzleey, Nur Zulfah Insyirah

    Published 2024
    “…Thus, this project aims to develop the best model detector for an automated vehicle classification system using computer vision and machine learning algorithms to enhance toll collection efficiency. …”
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    Book Chapter
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    Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language by Sutarman, .

    Published 2016
    “…The sample of 3D data coordinates of X, Y, and Z axis is a value relative to the torso and head. In this study, the images has been captured using a kinect sensor based skeletal algorithms. …”
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  14. 14

    Bacterial image analysis using multi-task deep learning approaches for clinical microscopy by Chin, Shuang Yee, Jian, Dong, Khairunnisa, Hasikin, Romano, Ngui, Lai, Khin Wee, Pauline Yeoh, Shan Qing, Xiang, Wu

    Published 2024
    “…The performance of the DL techniques is evaluated using the quantitative assessment method based on mean average precision (mAP), precision, recall, and F1-score. …”
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    Article
  15. 15

    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

    Published 2025
    “…For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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    Article
  16. 16

    An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

    Published 2024
    “…The study incorporating optimization strategy in semantic segmentation is underexplored in dermatology. Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
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    Article
  17. 17

    Feature detector-level fusion methods in food recognition by Razali @ Ghazali, Mohd Norhisham, Manshor, Noridayu

    Published 2019
    “…The features are encoded by using k-means clustering and Support Vector Machine with linear kernel has been employed for classification. …”
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    Conference or Workshop Item
  18. 18

    Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli by Rosli, Mohamed Syazwan Asyraf

    Published 2022
    “…In this research, several single-stage detectors of YOLO models namely as YOLOv3, YOLOv4, YOLOv5 including their subset models were evaluated for benchmarking and comparison purpose. …”
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  19. 19

    The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach by Taha, Z., Musa, R.M., Majeed, A.P.P.A, Abdullah, M.R., Zakaria, M.A., Alim, M.M., Jizat, J.A.M., Ibrahim, M.F.

    Published 2018
    “…Psychological coping skills inventory which evaluates the archers level of related coping skills were filled out by the archers prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. …”
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    Conference or Workshop Item
  20. 20

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…The neural network chosen in this study was multi-layer and back-propagation (BP) due to the ability to learn and determine nonlinear combinations. 70.0% of data were assigned for the purpose of training the network, while the remaining 30.0% of data were allocated for testing model accuracy.Subsequently in imaging processing study, 287 oil palm samples were classified into three disease levels (T1 to T3) using ANN, whereby the principle of the classification is to seek for the most representative image configurations and network properties while adjusting for the best canopy circle radius, threshold limit, best neuron numbers of hidden layer and the best mean and standard deviation values from different combination of spectral bands (green,red, and NIR bands) from CIR images obtained from a unmanned aerial vehicle (UAV). …”
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    Thesis