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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
Published 2024“…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile
“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures
Published 2024“…The algorithm’s distinctive feature lies in its ability to perform non-numeric computations, rendering it adaptable to intricate deep learning problems. …”
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques
Published 2022“…The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. …”
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An improved hybrid learning approach for better anomaly detection
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Investigating the relationship between the urban heat island effect and short-duration extreme rainfall in Kuala Lumpur
Published 2025“…LULC classification was performed using Support Vector Machine (SVM) and Random Forest (RF) algorithms, while LST was estimated using the Single Channel (SC) algorithm and surface urban heat island intensity (SUHII) was subsequently derived from the LST data. …”
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Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review
Published 2021“…We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…Even though at first glance the classification accuracy was moderate, the level of details provided by the imageries suggests that the accuracies were acceptable. …”
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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Thesis
