Search Results - (( _ segmentation using algorithm ) OR ( using factorization machine algorithm ))

A feature-based approach for segmenting faces by Zaqout, I., Zainuddin, R., Baba, S.

“…The algorithm detects feature points from the image and groups them into face candidates using geometric and grey level constraints. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…Then, an adaptive threshold and inequality criteria are used to eliminate most of the non-transition frames and preserve candidate segments. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…A dynamic actuator was used to cause damage in the tower segments by applying vibration force. …”
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Segmenting microcalcifications using enhanced distance active contour (EDAC) / Siti Salmah Yasiran by Yasiran, Siti Salmah

“…This study sets out to explore the Active Contour models to segment object boundaries using the Distance Active Contour (DAC) method. …”
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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

“…After that segmented region is classified into three types of skin lesion using hybrid features of Alex-Net and VGG-16 through the transfer learning approach. …”
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A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Classification and prediction of obesity levels among subjects in Colombia, Peru, and Mexico using unsupervised and supervised learning by Suhaila, Bahrom, Anuar, Ab Rani, Aisyah Amalina, Mohd Noor

“…This research investigates the multifaceted relationship between various factors and obesity rates in Mexico, Peru, and Colombia using a publicly available dataset. …”
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Using Machine Learning to Optimize Green Influencer Marketing Strategies: A Study of Consumer Behavior Trends by Neetu, Sharma

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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

“…The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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Smart Microgrid approach for Distributed power generation of renewable energy by Khushi, Farha, Motakabber, S. M. A., Ahmed Hamida, Belal, Azman, Amelia Wong, Bhattacharjee, Amit

“…The Faulty Location Detection (FLD) process is centered by wavelet trigger signal and mathematical morphology algorithm. In the method, the wavelet trigger signal caused by the equivalent current or voltage for a short time, travels to both terminals of the line are simulated to identify whether the fault occurs in the short branch using mathematical morphology algorithm. …”
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Image segmentation based on normalised cuts with clustering algorithm by Choong, Mei Yeen

“…With the approach applied in the normalised cuts based image segmentation, the constraint of using normalised cuts algorithm in image segmentation can be alleviated. …”
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An evolutionary harmony search algorithm with dominant point detection for recognition-based segmentation of online Arabic text recognition by Moayad, Yousif Potrus, Ngah, Umi Kalthum, Bestoun S. , Ahmed

“…At first, the pre-segmentation algorithm uses a modified dominant point detection algorithm to mark a minimal number of points which defines the text skeleton. …”
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Effects of Different Superpixel Algorithms on Interactive Segmentations by Soo See, Chai, Luong Goh, Kok, Weng Ng, Giap, Muzaffar, Hamzah

“…As such, the key to achieving a decent segmentation result lies in choosing the right superpixel algorithms for a given interactive segmentation algorithm.…”
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UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES by MOHAMMAD SAMEER ALOUN

“…The unsupervised segmentation of color-texture regions using J-value segmentation (JSEG) algorithm is one of the most popular and robust unsupervised segmentation algorithms. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA) by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Samsudin, Ruhaidah, Ameerbakhsh, Omair

“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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