Search Results - (( phone application learning algorithm ) OR ( _ application use algorithm ))
Search alternatives:
- application learning »
- learning algorithm »
- phone application »
- application use »
- use algorithm »
-
1
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
2
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
3
Distracted driver detection with deep convolution neural networks
Published 2023text::Final Year Project -
4
-
5
-
6
Innovative smart phone learning system for graphical systems within covid-19 pandemic
Published 2023“…Accordingly, this study�s main objective is to develop a model system that can function as smartphone computer graphics. This paper used the Technology Acceptance Model (TAM) as an m-learning model, and Bresenham�s line algorithm is a calculation system implemented by applications. …”
Article -
7
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
Get full text
Get full text
Thesis -
8
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
Get full text
Get full text
Article -
9
-
10
-
11
Malware visualizer: A web apps malware family classification with machine learning
Published 2021“…The objective of this project is to build a web apps to classify malware by transforming the apk file into image-based representation. This project uses three classification algorithm which are Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). …”
Get full text
Get full text
Conference or Workshop Item -
12
Mobile tour guide application with attraction recognition for UTAR Kampar campus
Published 2021Get full text
Get full text
Final Year Project / Dissertation / Thesis -
13
-
14
Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…The rapid growth of mobile phone technologies encourages many researchers to explore, design and develop mobile learning applications for tertiary students. …”
Get full text
Get full text
Conference or Workshop Item -
15
Mobile Learning: An Application Prototype for AVL Tree Learning Object
Published 2010“…The rapid growth of mobile phone technologies encourages many researchers to explore, design and develop mobile learning applications for tertiary students. …”
Get full text
Get full text
Get full text
Article -
16
Machine Learning Applications in Multiplayer Online Battle Arena Esports—A Systematic Review
Published 2025“…The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used for the analysis. Papers were included if they contained ML applications for MOBA, excluding game design or non-esports-related studies. …”
Get full text
Get full text
Get full text
Get full text
Article -
17
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
18
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
19
Enhanced notes capture using super resolution technique on tecogan
Published 2023Get full text
Get full text
Final Year Project / Dissertation / Thesis -
20
