Search Results - (( developing mobile extraction algorithm ) OR ( java implication based algorithm ))
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Overhead vision system for mobile robot orientation detection
Published 2011“…A simple neural network model is developed to estimate the orientation of the mobile robot. …”
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Thesis -
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Developing stereo vision system for object recognition and positioning of AMAD-R mobile robot
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Working Paper -
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
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Online Mapping-Based Navigation System for Wheeled Mobile Robot in Road Following and Roundabout
Published 2018“…A road mapping and feature extraction for mobile robot navigation in road roundabout and road following environments is presented in this chapter. …”
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Book Chapter -
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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Reduced Set Kernel Principal Component Analysis (Rskpca) Algorithm for Palm Print Based Mobile Biometric System
Published 2015“…In this study mobile biometric system based on palm print modality is developed. …”
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Thesis -
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Designing an expressive virtual Kompang on mobile device with tri-axial accelerometer
Published 2018“…Multiple features related to the shape of the drum hit are extracted by using tri-axis accelerometer sensors of the mobile device. …”
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization
Published 2024thesis::master thesis -
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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…From here, the extracted values are implied on k-NN, Decision Tree and CNN training algorithm. …”
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Development of portable automatic number plate recognition system on android mobile phone
Published 2013“…Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. …”
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Article -
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Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone
Published 2022“…In order to overcome these issues, a supervised Deep Neural Network (DNN) algorithm predicted constrained Wiener Filter (cWF) target mask algorithm based on extracted Gammatone filter bank power spectrum (GF-TF) features and trained model is developed. …”
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Thesis -
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Development of portable automatic number plate recognition system on android mobile phone
Published 2013“…Thus, the significance efforts are to find suitable and adaptive algorithm for number plate recognition under mobile phone. …”
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Proceeding Paper -
14
A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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A new mobile malware classification for SMS exploitation
Published 2024“…This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. …”
Conference Paper -
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Herb recognition for mobile apps / Jumriyanie Baba
Published 2017“…This project involves designing and developing on Herbs Recognition for Mobile Application. …”
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Thesis -
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…Too many features used, features extraction time consuming and the reliability of accuracy result by various machine learning algorithm are the main issues spotted in static analysis approach. …”
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Thesis -
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…The context model allows computing the mobile device intrinsic fingerprints for the source mobile device identification. …”
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Development of an intelligent multimodal biometric system for household appliances control
Published 2012“…In the first phase, individual biometrics recognition algorithms were developed for each biometrics feature. …”
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