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

“…Over the last decade, many algorithms have been developed to address this problem. …”
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Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

“…The PC-tree is a well-organized tree structure, which is systematically built based on descendant making introduced in this study. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction by Rashid, Mamunur, Bari, Bifta Sama, Yusri, Yusup, Mohamad Anuar, Kamaruddin, Khan, Nuzhat

“…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Advanced Processing of UPM-APSB’s AISA Airborne Hyperspectral Images for Individual Timber Species Identification and Mapping by Jusoff, Kamaruzaman

“…Kelat constituted the highest count of species (1,402) mapped followed by Kedondong (1,185 trees), Medang (1,116 trees) and others out of the total 13,861 trees. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Application of machine learning in analysing historical and non-historical characteristics of heritage pre-war shophouses / Nur Shahirah Ja’afar and Junainah Mohamad by Ja’afar, Nur Shahirah, Mohamad, Junainah

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, JULI RI ANDIKA, JULI RI ANDIKA, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

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An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

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Modeling purchase intention towards edible bird's nest products among Malaysians by Mohamad Shukri, Nurul Nabilah Huda, Mohd Nawi, Nolila, Abdullah, Amin Mahir, Man, Norsida

“…The three popular classification algorithms from predictive models which are decision tree, logistic regression, and artificial neural network will be used to analyze the dataset and determined the best model building. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. With large variability in SOM, the field presents a special situation and thus, the result could be specific to the study site. …”
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