Search Results - (( based segmentation using algorithm ) OR ( based validation study algorithm ))

Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

“…In this case, the algorithm of the DIS operator is embedded with the Marker-based Watershed segmentation as the assistance of Marker-based Watershed Segmentation is effective in extracting the individual significant edges features produced by DIS operator. …”
Get full text
Get full text

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

Get full text
Get full text

An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
Get full text
Get full text
Get full text

Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering by Abang Mohd Arif Anaqi, Abang Isa

“…Research has shown that an automated segmentation from the Magnetic Resonance Image (MRI) is potentially giving more effective and accurate results. This study aims to develop an automatic segmentation by utilizing clustering algorithm for acute ischemic stroke lesion identification. …”
Get full text
Get full text
Get full text

Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

“…Currently testing the validation of the proposed segmentation in a validation study that compares resulting MS lesion as well as gray and white matter tissue structures with Neural Network expert segmentation system. …”
Get full text
Get full text

Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

“…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. The solution consists of an algorithm for automatic collection of candidate seed points using efficient grid line searching mechanism and a validation method which uses local geometric and intensity based features as effective validation rules to discriminate between the actual seed point and false alarms. …”
Get full text
Get full text

Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah by Abdullah, Suzanah

“…The experiments were performed in both simulation and real site studies based on four algorithms namely inverse watershed segmentation (IWS), object-based image analysis (OBIA), watershed segmentation (WS) and seed generation (SG). …”
Get full text
Get full text

Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…The methodology is proposed as stacking ensemble ML and the best ML algorithms are used as a base learner to compute relative feature weights. …”
Get full text
Get full text

Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…This study validates the effectiveness of deep learning based segmentation methods for automated soil crack recognition and quantification, contributing to engineering applications with improved methodologies for analysing desiccation behaviour in expansive soils. …”
Get full text
Get full text

Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression by Tan, Li Kuo, McLaughlin, Robert A., Lim, Einly, Abdul Aziz, Yang Faridah, Liew, Yih Miin

“…Purpose: To develop and validate a fully automated neural network regression-based algorithm for segmentation of the LV in cardiac MRI, with full coverage from apex to base across all cardiac phases, utilizing both short axis (SA) and long axis (LA) scans. …”
Get full text
Get full text

Facial Feature Extraction Based on Improved Harris Corner Detection Algorithm by Bagherian, Elhaam

Get full text
Get full text

Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter by Taghvaee, Mohammad Hossein

“…Simulation results are presented to validate performance of the algorithm under different irradiation schemes, and to compare with the results obtained from conventional algorithm. …”
Get full text
Get full text

Automatic Road Network Recognition and Extraction for Urban Planning by Bong, David B L, Lai, K.C., Joseph, A.

“…The extracted road regions are validated by using a segmentation method. These results are valuable for building road map and detecting the changes of the existing road database. …”
Get full text
Get full text
Get full text

Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…The damage, due to uncontrolled noise reciprocating motion in the machines or broadband noise from wind or other sources, is identified based on frequency testing in an operator. Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
Get full text
Get full text

A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering by Prasetyadi, Abdurrakhman, Nugroho, Budi, Tohari, Adrin

“…Furthermore, applying the hybrid algorithm to the keyword segment and the type of disaster produced a homogeneous clustering as indicated by the calculated purity coefficient and the total purity values. …”
Get full text
Get full text
Get full text
Get full text

An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery by Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud

“…This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. …”
Get full text
Get full text
Get full text

Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

“…Background: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model. …”
Get full text
Get full text
Get full text
Get full text

A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

“…Thus, this study developed a novel deep learning oil spill detection model using computer vision instance segmentation Mask-Region-based Convolutional Neural Network (Mask R-CNN) model. …”
Get full text
Get full text

A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

“…Thus, this study developed a novel deep learning oil spill detection model using computer vision instance segmentation Mask-Region-based Convolutional Neural Network (Mask R-CNN) model. …”
Get full text
Get full text

Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

“…The developed U-Net architecture has been applied on the MRI scan brain tumor segmentation dataset in MICCAI BraTS 2017. The results using Matlab-based toolbox indicate that the proposed architecture has been successfully evaluated and experienced for MRI datasets of brain tumor segmentation including 336 images as training data and 125 images for validation. …”