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GSM based Communication-Sensor (CommSense) System
Published 2018“…We have compared two widely accepted supervised learning algorithms, called Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP). …”
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Designing a hyperinstrument with gesture interface for musical performance
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Deep learning based methods for tuberculosis cough classification
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Implementation of fast airborne synthetic aperture radar simulation
Published 2024“…Since nowadays the modem aircraft may be fitted with SAR facility, the aim of this dissertation is to develop fast algorithms for a fast or real-time like SAR simulator which could aid in airplane pilot training. …”
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Evaluating digital image correlation speckle pattern quality using finite element‑based displacement fields
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Application of convolutional neural networks to building segmentation in aerial images
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User Profiling through Zero-Permission Sensors and Machine Learning
Published 2023“…We then pass this processed training data through machine learning algorithms, enabling accurate user profiling without the need for explicit information gathering. …”
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Fusion of phoneme recognisers for South African English
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Wheat and triticale whole grain near infrared hyperspectral imaging for protein, moisture and kernel hardness quantification
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Quantum Machine Learning Applied to Astronomical Datasets
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Practical Lane Detection for Medium-to-High Density Traffic in Unstructured or Partially Occluded Roads
Published 2024“…Develop a framework for a new research topic: The Practical-Lane Detection. 2. Develop an algorithm to model practical-lanes based on vehicles observed on the road with respect to a reference car. 3. …”
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Predicting mire distribution using species distribution models (SDMs) and GISc : a case study of the Prince Edward Islands (PEIs)
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Design of a centrifugal compressor impeller for micro gas turbine application
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Hydraulic Data Preprocessing for Anomaly Based Intrusion Detection on SCADA Level of Water Treatment Systems
Published 2024“…The best performance was achieved when the preprocessed dataset was randomly split into training and testing, yielding a significant improvement in accuracy, F1 score and time to detection for both algorithms used in the study, namely Fine Tree and Boosted Trees Ensemble.…”
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