Search Results - (( _ evaluation from algorithm ) OR ( early classification system algorithm ))

Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…To improve the performance from current systems, this work has investigation on different of image pre-processing enhancement technique to support accuracy on deep learning for DR classification. …”
Get full text
Get full text

Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

“…The proposed algorithms that outperformed the state-of-the-art algorithms contributes to diagnosing early-stage Melanoma. …”
Get full text
Get full text
Get full text

Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

“…As the results, the accuracy of CNN classification has improved at least 6 percent compared to the conventional algorithms.…”
Get full text
Get full text
Get full text

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

“…To measure the result of algorithm developed, dice coefficient (DC) is the metric that is chosen to measure the accuracy of algorithm; Dice similarity coefficient (DSC) was used as a statistical validation metric to evaluate the performance of both the reproducibility of manual segmentations and the spatial overlap accuracy of automated probabilistic fractional segmentation of ultrasound images. …”
Get full text
Get full text

Classification of Mammogram Images Using Radial Basis Function Neural Network by Ashraf Osman, Ibrahim, Ali, Ahmed, Aleya, Abdu, Rahma, Abd-alaziz, Mohamed Alhaj, Alobeed, Abdulrazak Yahya, Saleh, Abubakar, Elsafi

“…This method is focused on features extracted from the breast cancer mammogram image processing algorithms. …”
Get full text
Get full text
Get full text

Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm by Molla, M. M. Imran, Jui, Julakha Jahan, Bari, Bifta Sama, Rashid, Mamunur, Hasan, Md Jahid

Get full text
Get full text
Get full text
Get full text

Mental health detection based on facial recognition using CNN algorithm / Muhammad Azim Azfar Rozihan by Rozihan, Muhammad Azim Azfar

Get full text
Get full text

Classification of Learner Retention using Machine Learning Approaches by Nur Amalina Diyana Suhaimi , Norshaliza Kamaruddin, Thirumeni T Subramaniam, Nilam Nur Amir Sjarif, Maslin Masrom, Nurazean Maarop

“…The performance of these algorithms was evaluated based on accuracy, precision, recall, and f-measure. …”
Get full text
Get full text

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…This study addresses this gap by leveraging data from the Behavioral Risk Factor Surveillance System (BRFSS)from 2016 to 2021 to categorize seven diabetes complications simultaneously. …”
Get full text
Get full text

Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

“…Additionally, the SVM algorithm was evaluated based on its performance across different DWI bvalues, aiming to optimize scanning time. …”
Get full text
Get full text
Get full text

Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…The Edited Nearest Neighbour technique, shown to be effective in other O&G subdomains, is evaluated using the Random Forest algorithm, which is widely used for its precision and ability to handle non-linear datasets. …”
Get full text
Get full text

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. …”
Get full text
Get full text

Flood prediction model for Kuala Terengganu area using predictive analytics by Mohd Zamri, Najwa An-Nisa

“…Three classification algorithms were tested: Decision Tree, Naive Bayes, and Random Forest. …”
Get full text
Get full text

Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
Get full text
Get full text
Get full text

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

“…In conclusion, for early detection of Ganoderma, better accuracies were derived from the spectroradiometer which is a destructive and ground based method and still requires individual leaf sampling. …”
Get full text
Get full text
Get full text

Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

“…Several combinations of epochs, learning rates, and optimisation algorithms were tested to enhance performance. Model evaluation metrics included accuracy, precision, recall, and F1-score. …”
Get full text
Get full text
Get full text

Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features by Acharya, U. Rajendra, Koh, Joel En Wei, Hagiwara, Yuki, Tan, Jen Hong, Gertych, Arkadiusz, Vijayananthan, Anushya, Yaakup, Nur Adura, Abdullah, Basri Johan Jeet, Mohd Fabell, Mohd Kamil, Yeong, Chai Hong

“…Our automated CAD system can differentiate normal, malignant, and benign liver lesions using machine learning algorithms. …”
Get full text
Get full text

A Semi-Automatic Approach for Thermographic Inspection of Electrical Installations Within Buildings by M. S., Jadin, A. S., Nazmul Huda, Soib, Taib, Dahaman, Ishak

“…The performances of multilayered perceptron networks have been compared and tested with various training algorithms. The classification accuracy of multilayered perceptron networks are also compared with discriminant analysis classifier and it is found that the multilayered perceptron network using Levenberg–Marquardt algorithm gives the best testing performance. …”
Get full text
Get full text
Get full text

Deep learning-based recommendation system to address challenges in providing electronic services by AL Hinai, Turki Abdullah Masood, Al Kulaibi, Juma, Al Husaini, Mohammed Abdulla Salim, Al Husaini, Yousuf Nasser, Habaebi, Mohamed Hadi

“…The SVM algorithm, known for its robust classification capabilities in high-dimensional spaces, was implemented using MATLAB R2023b and evaluated on a system with an Intel Core i7 (14th Gen), 32 GB RAM, and an NVIDIA RTX 4070 GPU. …”
Get full text
Get full text
Get full text

Ensemble learning of deep learning and traditional machine learning approaches for skin lesion segmentation and classification by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, Hiren, Mewada, Muhammad Abid, Sherazi

“…We extract the features through traditional split and merge approach as well as from deep learning algorithms of contextual encoding along with the attention mechanism. …”
Get full text
Get full text
Get full text
Get full text