Search Results - (( basic detection method algorithm ) OR ( evolution classification modeling algorithm ))
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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Proceeding Paper -
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Deep learning detector for pests and plant disease recognition
Published 2020“…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Final Year Project / Dissertation / Thesis -
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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Thesis -
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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Conference or Workshop Item -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Thesis -
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Article -
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Cars detection in stitched image using morphological approach
Published 2017“…The performance of the proposed cars detection algorithm could detect the cars fairly accurate. …”
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Final Year Project Report / IMRAD -
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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Book Section -
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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Article -
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An ensemble feature selection method to detect web spam
Published 2018“…An ensemble feature selection method has been proposed in this paper to detect web spam. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Article -
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Enhanced algorithms for three-dimensional object interpreter
Published 2004“…The linear system is solved using bisection method of total least square approximation. Besides reducing the number of image regularities used and new method to solve the linear system, this study has proposed better solutions in terms of an enhanced thinning algorithm, a modified Freeman chain code algorithm as picture description language, and a new computational comer detection algorithm.…”
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Thesis -
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Thalassaemia detection using CBR Algorithm via mobile device
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Undergraduates Project Papers -
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation
Published 2024thesis::master thesis -
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Web Camera Application For Motion Detection
Published 2003“…The new method to detect motion is "vision motion detection". …”
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Thesis -
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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