Search Results - (( mobile evaluation _ algorithm ) OR ( text classifications using algorithmic ))
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Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
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ChoCD : Usable and secure graphical password authentication scheme
Published 2024thesis::master thesis -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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A new mobile malware classification for call log exploitation
Published 2024journal::journal article -
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Optimizing the performance of mobile malware detection using the indexing rule
Published 2024journal::journal article -
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“myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.]
Published 2020“…In addition, it also contributes to the exploration and implementation of learning algorithm in mobile-based application.…”
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Hybrid intelligent approach for network intrusion detection
Published 2015“…Then, a features selection algorithm is applied to remove irrelevant and noisy features for the purpose of intrusion. …”
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Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah
Published 2021“…The architecture is also evaluated based on the performance produced by experiments conducted using different combination of hyperparameters. …”
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Classification for Quran authentication using characters and diacritics hashed values
Published 2024journal::journal article -
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Convolutional neural network based mobile application for poisonous mushroom detection
Published 2025“…To address these issues, this study aims to develop a mushroom detection prototype specifically for identifying poisonous mushrooms using a mobile application. The application leverages a Convolutional Neural Network (CNN) algorithm to accurately classify mushrooms based on user-submitted images. …”
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Article -
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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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The prediction of stock management for Farmasi Chendering
Published 2025“…This project focuses on Farmasi Chendering, aiming to develop a predictive stock management system using ABC-VEN analysis and the J48 decision tree algorithm. The adapted CRISP-DM methodology guided the development process, encompassing data preparation, modeling, evaluation, and deployment. …”
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Student Project -
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…In the methodology, this study discloses five useful stages. Firstly, mobile phone users' irregular walking behaviour is investigated using a questionnaire to determine their options on mobile usage in the street. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…In the methodology, this study discloses five useful stages. Firstly, mobile phone users' irregular walking behaviour is investigated using a questionnaire to determine their options on mobile usage in the street. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…In addition, the results from the three (3) algorithms that were tested showed that Random Forest outperforms other algorithms by acquiring an accuracy and classification error to predict reverse migration. …”
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Auto-formation group chat for fitness application with rule-based / Amar Aslam Ramli
Published 2018“…Lastly, added some features such as include the registration in the android mobile application system as ease users to register instead of register in the website system.…”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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