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1
Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…The aim of this study was to produce a land cover map on the distribution of oil palm plantations on three districts located in Selangor. Landsat 8 images of resolutions 15 x 15 m were used and classified via machine learning and non-machine learning algorithms. …”
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2
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…Soft computing techniques, such as bio-inspired algorithms, can be used for information processing by employing methods which are capable to deal with imprecision and uncertainty. …”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review
Published 2024“…Furthermore, it is also shown that various machine learning algorithms are used, and the most used are Neural Network and Support Vector Machine. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method
Published 2015“…In the literature, mostly statistical and machine learning methods are used individually; however, their integration can enhance the final output. …”
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10
Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…Support Vector Machine (SVM) used to classify frames according to findings. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…Support Vector Machine (SVM) used to classify frames according to findings. …”
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12
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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Evaluation of machine learning in predicting air quality index / Abdullah Sani Abdul Rahman, Aizal Yusrina Idris and Suhaimi Abdul Rahman
Published 2023“…Three machine learning algorithms, namely Generalized Linear Model, Decision Tree and Support Vector Machine are used in this research. …”
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Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania
Published 2025“…We used 158 flood locations as dependent variables in the training of four hybrid models: Deep Learning Neural Network-Statistical Index (DLNN-SI), Particle Swarm Optimization-Deep Learning Neural Network-Statistical Index (PSO-DLNN-SI), Support Vector Machine-Statistical Index (SVM-SI), and Particle Swarm Optimization-Support Vector Machine-Statistical Index (PSO-SVM-SI). …”
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Fault location identification in power transmission networks: using novel nonintrusive fault-monitoring systems
Published 2021“…After the processes of feature selection, the fault-location indicator is recognized by the support vector machines (SVMs). …”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency
Published 2018“…Aims: This research aims to improve automated brain MR image classification and tumor segmentation using phase congruency. Methods: The skull part is removed from brain MR image by applying converging square algorithm and phase congruency based edge detection method. …”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…Thus, the suitability map of potential hospital sites was modeled using a support vector machine (SVM), multilayer perceptron (MLP), and linear regression (LR) models. …”
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COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM
Published 2011“…Subsequently, a region growing algorithm was used to locate the pectoral muscle and suppress it from the breast. …”
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. …”
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