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An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification
Published 2024“…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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RGB and RGNIR image dataset for machine learning in plastic waste detection
Published 2025“…The increasing volume of plastic waste is an environmental issue that demands effective sorting methods for different types of plastic. …”
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Fault detection and diagnosis for gas density monitoring using multivariate statistical process control
Published 2011“…Therefore, an efficient fault detection and diagnosis algorithm needs to be developed to detect faults that are present in a process and pinpoint the cause of these detected faults. …”
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PCB defect detection system using run-length encoding
Published 2017“…The secondary objective is to design run-length encoding algorithm able to detect and classify the defect of printed circuit board (PCB). …”
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Snort-based smart and swift intrusion detection system
Published 2018“…Methods/Statistical Analysis: The features are extracted using back-propagation algorithm. …”
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Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques
Published 2024“…By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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Final Year Project / Dissertation / Thesis -
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…The model was applied to optimize the particle size of the transdermal nanoemulsion system containing an extract of C. nutans leaves for skin antiaging. Five universal learning algorithms—incremental back propagation, batch back propagation, quick propagation, genetic algorithm, and Levenberg-Marquardt—were used in the ANN to achieve the optimum topologies. …”
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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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Book Section -
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Thesis -
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. However, for the non-intact leaves such as the deformed, partial and overlapped leaves that largely exist in practice, the global shape features are not efficient and these methods are not applicable.The dried leave parts and noise can degrade identification results and affect the quality of the extracted features which lead to poor classification results. …”
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The comparative study of model-based and appearance based gait recognition for leave bag behind
Published 2018“…This research limited to leave the bag behind detection on gait recognition. …”
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023Conference Paper -
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Evaluation of diagnostic performance of rK28 ELISA using urine for diagnosis of visceral leishmaniasis
Published 2016“…Although simple, these tests still require blood collection and their use in remote settings can be limited due to the need of collection devices, serum fractionation instrument and generation of biohazardous waste. The development of an accurate and non-invasive diagnostic algorithm for VL, such as could be achieved with urine, is desirable. …”
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