Search Results - (( model evaluation means algorithm ) OR ( image classification using algorithm ))*
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
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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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
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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Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
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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Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran
Published 2023“…The object detection and classification algorithm achieved 91.9% mean average precision in metric evaluation. …”
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The classification of wink-based eeg signals by means of transfer learning models
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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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
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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Deep learning-based breast cancer detection and classification using histopathology images / 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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Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works
Published 2025Conference paper -
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…The k-means clustering algorithm is then applied to group visually similar chart images. …”
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Automated Vehicle Classification (AVC) using machine learning implementation in Malaysia's toll system
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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Automated mold defects classification in paintings: a comparison of machine learning and rule-based techniques.
Published 2025“…The efficacy of these methods was evaluated using the Mold Features Dataset (MFD) and a separate set of test images. …”
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
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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Bacterial image analysis using multi-task deep learning approaches for clinical microscopy
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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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images
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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An Optimized Semantic Segmentation Framework for Human Skin Detection
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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Feature detector-level fusion methods in food recognition
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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Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli
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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The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach
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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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
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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