Search Results - (( data application using algorithm ) OR ( parameter detection learning algorithm ))
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Early detection of dengue disease using extreme learning machine
Published 2018“…The availability of nowadays clinical data of Dengue disease can be used to train machine learning algorithm in order to automaticaly detect the present of Dengue disease of the patients. …”
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2
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…In this paper, an evaluation for these transfer learning to be applied in wafer defect detection. The objective is to establish the best transfer learning algorithms with a known baseline parameter for Wafer Defect Detection. …”
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Conference or Workshop Item -
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying
Published 2019“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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Federated deep learning for automated detection of diabetic retinopathy
Published 2022“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Proceeding Paper -
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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7
Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE
Published 2012“…However, DL has number of weaknesses as well, including difficulty in interpreting its examples (the 'black-box' criticism), its requirement for multiple training data, no specificity in design, no data-usefulness in training, limited use in experimental models, and so on. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…Backpropagation is used as the learning method of ANN model. The algorithm will be developed in MATLAB. …”
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10
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD)
Published 2022“…This study indicates developing an algorithm for detecting and progressing through the hippocampus of patients with Alzheimer's disease in MRI images. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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13
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
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14
Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques
Published 2023“…The second contribution to this research is to develop multiple hybrid machine learning models in order to enhance the detection of fraudulent activities in the credit card fraud detection domain.…”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models
Published 2024“…These works have shown that, despite using only the optical chromaticity of the chicken comb as the input data, the developed models (95% accuracy) have performed exceptionally well, compared to other reported results (99.469% accuracy) which utilize more sophisticated input data such as morphological and mobility features. …”
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Early Detection of Cardiovascular Disease Using Photoplethysmography (PPG) Signal Analysis
Published 2024“…This study leverages machine learning techniques to enhance the accuracy of CVD detection from PPG data, addressing critical risk factors such as hypertension and stress, which significantly contribute to elevated blood pressure and, consequently, to cardiovascular disorders. …”
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Water quality monitoring using machine learning and IoT: a review
Published 2024“…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0
Published 2023“…In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. …”
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Final Year Project / Dissertation / Thesis
