Search Results - (( image classification using algorithm ) OR ( using function machine algorithm ))
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…This study investigates a new approach in image classification. Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). …”
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Support vector classification of remote sensing images using improved spectral Kernels
Published 2008“…A very important task in pattern recognition is the incorporation of prior information into the learning algorithm. In SUppOlt vector machines this task is performed via the kernel function. …”
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain
Published 2020“…From the accuracy test, SVM are proven to be one of the best classifier to classify the image data. For the future work, this system need to be improved by using dataset that are related to the ASD and by using other classification algorithm.…”
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Diagnosis and treatment recommender system for myocardial infarction using decision tree and Support Vector Machines (SVM) / Wan Marzuqiamrin Wan Mansor
Published 2025“…The prototype functions by initially allowing the user to upload an ECG image which will be processed using SVM for feature extraction and classification. …”
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Final Year Project / Dissertation / Thesis -
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Texture-based classification of workpiece surface images using the support vector machine
Published 2015“…Machine vision can be used to semi- or fully automate this identification process by firstly extracting features from captured workpiece images, followed by analysis using machine learning algorithms. …”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency
Published 2018“…MRI which stands for Magnetic Resonance Imaging is commonly used to capture images of internal body organs, functionality and structure. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…To overcome such challenges, this study attempts to comprehend and improve the remote sensing technology for rooftop classification using the Worldview-3 (WV-3) image and object-based image analysis (OBIA) method. …”
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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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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…Object extraction and object recognition are typical applications that use segmentation as a low level image processing. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The idea is to use GP to optimize the SVM decision function such that the minority class classification rate is increased without sacrificing the accuracy rate for both classes. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
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Early Detection Of ADHD Among Children Using Machine Learning
Published 2023“…By measuring brain activity patterns, fMRI provides insights into the functional abnormalities associated with ADHD. Machine learning algorithms can analyze fMRI data and identify biomarkers indicative of ADHD, enabling accurate classification. …”
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Undergraduates Project Papers -
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A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah
Published 2012“…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Comparison of machine learning classifiers for dimensionally reduced fMRI data using random projection and principal component analysis
Published 2019“…In addition to that, six different types of machine learning algorithm have been used. In particular, the Haxby dataset is chosen for our experiment. …”
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Proceeding Paper -
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…In this research, a new carving framework is presented in order to address the fragmentation issues that often occur in JPEG images which is called RX_myKarve. The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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