A
Asim Zeb
Researcher at Abbottabad University of Science and Technology
Publications - 27
Citations - 579
Asim Zeb is an academic researcher from Abbottabad University of Science and Technology. The author has contributed to research in topics: Wireless sensor network & Computer science. The author has an hindex of 9, co-authored 23 publications receiving 204 citations. Previous affiliations of Asim Zeb include Universiti Teknologi Malaysia & Hosei University.
Papers
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Journal ArticleDOI
Edge AI-Based Automated Detection and Classification of Road Anomalies in VANET Using Deep Learning
Rozi Bibi,Yousaf Saeed,Asim Zeb,Taher M. Ghazal,Taj Ur Rahman,Raed A. Said,Sagheer Abbas,Munir Ahmad,Muhammad Adnan Khan +8 more
TL;DR: In this paper, the authors used Residual Convolutional Neural Network (ResNet-18) and Visual Geometry Group (VGG-11) for road anomaly detection.
Journal ArticleDOI
Clustering Analysis in Wireless Sensor Networks: The Ambit of Performance Metrics and Schemes Taxonomy
Asim Zeb,A. K. M. Muzahidul Islam,Mahdi Zareei,Ishtiak Al Mamoon,Nafees Mansoor,Sabariah Baharun,Yoshiaki Katayama,Shozo Komaki +7 more
TL;DR: In this article, a wireless sensor network (WSN) has increased tremendously throughout the years, and sensor nodes are deployed to operate autonomously in remote environments in WSNs.
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A Machine Learning Approach for Blockchain-Based Smart Home Networks Security
Muhammad Adnan Khan,Sagheer Abbas,Abdur Rehman,Yousaf Saeed,Asim Zeb,M. Irfan Uddin,Nidal Nasser,Asmaa Ali +7 more
TL;DR: This paper introduces a resource-efficient, blockchain-based solution for secure and private IoT, made possible through novel exploitation of computational resources in a typical IoT environment, along with the use of Deep Extreme Learning Machine (DELM).
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Prediction of Future Terrorist Activities Using Deep Neural Networks
M. Irfan Uddin,Nazir Zada,Furqan Aziz,Yousaf Saeed,Asim Zeb,Syed Atif Ali Shah,Mahmoud Ahmad Al-Khasawneh,Marwan Mahmoud +7 more
TL;DR: Five different models based on deep neural network (DNN) are created to understand the behavior of terrorist activities and it is demonstrated that the performance in DNN is more than 95% in terms of accuracy, precision, recall, and F1-Score, while ANN and traditional machine learning algorithms have achieved a maximum of 83% accuracy.
Journal ArticleDOI
Modeling, Simulation and Optimization of Power Plant Energy Sustainability for IoT Enabled Smart Cities Empowered With Deep Extreme Learning Machine
Sagheer Abbas,Muhammad Adnan Khan,Luis Eduardo Falcón-Morales,Abdur Rehman,Yousaf Saeed,Mahdi Zareei,Asim Zeb,Ehab Mahmoud Mohamed +7 more
TL;DR: The method of a deep extreme learning machine is explored to create a predictive model that can predict a combined cycle power plant’s hourly full-load electrical output and it is shown that the proposed approach has the highest accuracy rate.