Search Results - (( _ evaluation focus algorithm ) OR ( image classification learning algorithm ))

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

“…Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm.…”
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Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works by Moktar M.H., Hajjaj S., Mohamed H., Weng L.Y.

Subjects: “…Image enhancement…”

Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

“…This study investigates the efficacy of staging classification using diffusion-weighted imaging magnetic resonance imaging (DWIMRI) through radiomic analysis and machine learning. …”
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Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

“…The methods of image spam classification as identified in this study are supervised machine learning, unsupervised machine learning, semi-supervised machine learning, content-based and statistical learning. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…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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Comparative analysis of convolutional neural network frameworks for efficient classification of calcification patches in Digital Breast Tomosynthesis images / Nurhazwani Mohamad Fo... by Mohamad Fozi, Nurhazwani

“…Early detection significantly reduces fatality rates, motivating the development of deep learning algorithms for medical imaging analysis. Calcifications are the most important subject in early stages of breast cancer detection. …”
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Machine learning-based change detection for land use land cover in Malaysia by Mohd Noor, Muhammad Fareed, Rahmat, Noor Zarikh Khuzaimi, Abdullah, Nur Azam, Mohd Ibrahim, Azhar, Al Mahmud, Suaib, Mardzuki, Muhammad Imran

“…For supervised classification, Support Vector Machine (SVM), Classification and Regression Tree (CART), and Random Forest classifiers were tested. After thorough evaluation, it was determined that the Random Forest algorithm was the optimal choice, yielding a training accuracy of 99.6% and a test accuracy of 80% for LULC classification. …”
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Machine learning or morphometric scaling? a systematic review of methodological confounds and the generalizability of sex classification in neuroimaging by Sapuan, Abdul HaliM, Jamaludin, Iqbal, Abdul Majid, Zafri Azran, Mohd Tamrin, Mohd Izzuddin, Che Azemin, Mohd Zulfaezal, Turaev, Sherzod

“…We examine how imaging modalities, algorithms, and population strata influence both classification outcomes and biological interpretability. …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The accuracy of 2D tumor detection and segmentation are increased, enabling more 3D detection, and achieving a mean classification accuracy of 98 across system records. Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
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Semantic focus fusion based on deep learning for deblurring effect by Ismail, .

“…Due to the limited depth of field (DOF) of camera lens, the camera cannot generate high-quality images without blurred region images. In a rapid development of intelligent computation, such as deep learning algorithm, multi-focus image fusion methods indirectly being involved, such as CNN and PCA Net architectures. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

“…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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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

“…Conclusions This study has demonstrated the effectiveness, potential, and applicability of DL approaches in multi-task bacterial image analysis, focusing on automating the detection and classification of bacteria from microscopic images. …”
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Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability by M. Muslim, Ali

“…This was based on machine learning and regression algorithms at the first phase. …”
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Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

“…The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. …”
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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

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Classification of brain tumors: using deep transfer learning by Husin, Nor Azura, Husam, Mohamed, Hussin, Masnida

“…Experimenters employed data augmentation and learning algorithms.…”
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