Latifah Almuqren

Orcid: 0000-0001-6815-926X

According to our database1, Latifah Almuqren authored at least 20 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Efficient android malware identification with limited training data utilizing multiple convolution neural network techniques.
Eng. Appl. Artif. Intell., January, 2024

A Novel Deep Learning Architecture for Agriculture Land Cover and Land Use Classification from Remote Sensing Images Based on Network-Level Fusion of Self-Attention Architecture.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

Contradiction in text review and apps rating: prediction using textual features and transfer learning.
PeerJ Comput. Sci., 2024

Arabic Text Sentiment Analysis: Reinforcing Human-Performed Surveys with Wider Topic Analysis.
CoRR, 2024

Enhancing Red Palm Weevil Detection Using Bird Swarm Algorithm With Deep Learning Model.
IEEE Access, 2024

Optimal Deep Learning Empowered Malicious User Detection for Spectrum Sensing in Cognitive Radio Networks.
IEEE Access, 2024

2023
IoT and Ensemble Long-Short-Term-Memory-Based Evapotranspiration Forecasting for Riyadh.
Sensors, September, 2023

A White Shark Equilibrium Optimizer with a Hybrid Deep-Learning-Based Cybersecurity Solution for a Smart City Environment.
Sensors, September, 2023

Predicting STC Customers' Satisfaction Using Twitter.
IEEE Trans. Comput. Soc. Syst., February, 2023

Sine-Cosine-Adopted African Vultures Optimization with Ensemble Autoencoder-Based Intrusion Detection for Cybersecurity in CPS Environment.
Sensors, 2023

Blockchain-Assisted Secure Smart Home Network Using Gradient-Based Optimizer With Hybrid Deep Learning Model.
IEEE Access, 2023

Hybrid Metaheuristics With Machine Learning Based Botnet Detection in Cloud Assisted Internet of Things Environment.
IEEE Access, 2023

Blockchain-Assisted Vehicle and Cargo Matching Using Optimal Fuzzy Restricted Boltzmann Machine in Autonomous Transport System.
IEEE Access, 2023

2021
AraCust: a Saudi Telecom Tweets corpus for sentiment analysis.
PeerJ Comput. Sci., 2021

An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach.
Future Internet, 2021

COVID-19's Impact on the Telecommunications Companies.
Proceedings of the Trends and Applications in Information Systems and Technologies, 2021

2019
Using Deep Learning Networks to Predict Telecom Company Customer Satisfaction Based on Arabic Tweets.
Proceedings of the Information Systems Development: Information Systems Beyond 2020, 2019

2017
A Review on Corpus Annotation for Arabic Sentiment Analysis.
Proceedings of the Social Computing and Social Media. Applications and Analytics, 2017

2016
Twitter Analysis to Predict the Satisfaction of Telecom Company Customers.
Proceedings of the Late-breaking Results, 2016

Framework for Sentiment Analysis of Arabic Text.
Proceedings of the 27th ACM Conference on Hypertext and Social Media, 2016


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