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Adversarial Attacks for Image Segmentation on Multiple Lightweight Models
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Due to the powerful ability of data fitting, deep neural networks have been applied in a wide range of applications in many key areas. However, in recent years, it was found that some adversarial samples easily fool the ...
Using machine learning to analyze the impact of coronavirus pandemic news on the stock markets in GCC countries
(
Elsevier
, 2022 , Article)
COVID-19 has resulted in high volatility in financial markets across the world. The goal of this study is to investigate the impact of COVID-19-related news on the stock markets in Gulf Cooperation Council (GCC) countries. ...
Millimeter Wave MIMO-OFDM with Index Modulation: A Pareto Paradigm on Spectral- Energy Efficiency Trade-Off
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) has recently received increased attention, due to the potential advantage to balance the trade-off between ...
Applications of deep learning for phishing detection: a systematic literature review
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Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
Phishing attacks aim to steal confidential information using sophisticated methods, techniques, and tools such as phishing through content injection, social engineering, online social networks, and mobile applications. To ...
StEduCov: An Explored and Benchmarked Dataset on Stance Detection in Tweets towards Online Education during COVID-19 Pandemic
(
MDPI
, 2022 , Article)
In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online education during the COVID-19 pandemic. StEduCov consists of 16,572 tweets gathered over 15 months, from March 2020 to May ...
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
To assist policymakers in making adequate decisions to stop the spread of the COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance. This paper presents a deep learning approach to ...
Using virtual reality to allow paramedics to familiarise themselves with a new ambulance patient compartment design
(
Hamad bin Khalifa University Press (HBKU Press)
, 2021 , Article)
Background: Virtual reality (VR) is still an evolving domain that presents a versatile medium to simulate various environments and scenarios that can be easily reset between users, which can be particularly useful for ...
Green internet of things using UAVs in B5G networks: A review of applications and strategies
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Elsevier B.V.
, 2021 , Article)
Recently, Unmanned Aerial Vehicles (UAVs) present a promising advanced technology that can enhance people life quality and smartness of cities dramatically and increase overall economic efficiency. UAVs have attained a ...
FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning
(
Elsevier
, 2022 , Article)
Federated Learning (FL) is a promising distributed training model that aims to minimize the data sharing to enhance privacy and performance. FL requires sufficient and diverse training data to build efficient models. Lack ...
System log detection model based on conformal prediction
(
MDPI AG
, 2020 , Article)
With the rapid development of the Internet of Things, the combination of the Internet of Things with machine learning, Hadoop and other fields are current development trends. Hadoop Distributed File System (HDFS) is one ...