Search Results - (( data extraction method algorithm ) OR ( data visualization learning algorithm ))
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…A critical step in developing such intelligent systems is the feature extraction process. Feature extraction is essential in classification, especially for data sources in the form of images. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Academic Exercise -
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. …”
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Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R
Published 2020“…Having documentation on the dashboard report also has been an issue when executive need to extract information manually from the dashboard. Besides, this paper also enlightens on one of the Machine Learning tools used which is R, with the utilization of K Nearest Neighbor (KNN) algorithm as method of classification for data. …”
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Final Year Project -
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Machine learning application for concrete surface defects automatic damage classification
Published 2024“…The aim of this research is to increase the efficiency of concrete surface defect analysis in terms of quality, time and cost. 200 images were collected, with 50 images for each concrete defect (crack, corrosion, spalling, and no defect) serving as control data. The Gray Level Co-Occurrence Matrix (GLCM) is used to create an image processing and feature extraction algorithm. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…The proposed methodology involves collecting wafer inspection data, extracting relevant features, and applying the GSSL algorithm to identify the hidden defects. …”
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Thesis -
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…Visualization through charts has become a crucial method for presenting complex data in a clear and structured format, surpassing traditional representation techniques in both clarity and interpretability. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…EEG signals such as visual evoked potential (VEP) is unique but highly uncertain and difficult to process.There exists no consistant agreement on suitable feature extraction methods and VEP electrodes in the past literature. …”
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ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
Published 2014“…The accuracy of the proposed neural network is compared with various feature extraction methods and feedforward learning algorithms. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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Thesis -
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Content-based indexing of low resolution documents
Published 2016“…The proposed identification and indexing method in the thesis uses a Visual Signature (VS). …”
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Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper analyzed several visual analytics ap- proach instantiated in machine learning algorithm for medical record analytics. …”
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Proceeding Paper -
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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