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An improved algorithm for iris classification by using support vector machine and binary random machine learning
Published 2018“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Thesis -
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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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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…The k-means clustering algorithm is then applied to group visually similar chart images. …”
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Automated Bird Species Identification Through Machine Learning Techniques
Published 2024“…In recent years, machine learning algorithms and pre-trained models such as ResNet, Histogram of Oriented Gradients (HOG), and Scale-Invariant Feature Transform (SIFT) have shown significant promise in automating bird species classification. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R
Published 2020“…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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Machine learning application for concrete surface defects automatic damage classification
Published 2024“…This model is trained using 80% of the image data and tested using another 20% of the image data. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Conference or Workshop Item -
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, with the goal of improving the recognition of minority sentiment classes. …”
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…Subsequently, we optimize machine learning sentiment classification by employing data augmentation in conjunction with feature engineering strategies, to improve the recognition of minority sentiment classes. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The blockage of the pump inlet could result in cavitation or mechanical parts breakdown which would increase the maintenance cost. Machine Learning is one of the ways as a preventive method by applying the data collected from the clogging experiment in the vibration lab to build up a machine learning model for classification of flow blockage levels in the centrifugal pump. …”
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Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning
Published 2022“…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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Final Year Project / Dissertation / Thesis -
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Undergraduates Project Papers -
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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