Big data and IoT-based applications in smart environments: A systematic review
This paper reviews big data and Internet of Things (IoT)-based applications in smart
environments. The aim is to identify key areas of application, current trends, data …
environments. The aim is to identify key areas of application, current trends, data …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
A novel CNN-LSTM-based approach to predict urban expansion
Time-series remote sensing data offer a rich source of information that can be used in a wide
range of applications, from monitoring changes in land cover to surveillance of crops …
range of applications, from monitoring changes in land cover to surveillance of crops …
RS-DCNN: A novel distributed convolutional-neural-networks based-approach for big remote-sensing image classification
Developments in remote sensing technology have led to a continuous increase in the
volume of remote-sensing data, which can be qualified as big remote sensing data. A wide …
volume of remote-sensing data, which can be qualified as big remote sensing data. A wide …
A novel hybrid deep learning model for detecting COVID-19-related rumors on social media based on LSTM and concatenated parallel CNNs
Spreading rumors in social media is considered under cybercrimes that affect people,
societies, and governments. For instance, some criminals create rumors and send them on …
societies, and governments. For instance, some criminals create rumors and send them on …
Randomly initialized convolutional neural network for the recognition of COVID‐19 using X‐ray images
By the start of 2020, the novel coronavirus (COVID‐19) had been declared a worldwide
pandemic, and because of its infectiousness and severity, several strands of research have …
pandemic, and because of its infectiousness and severity, several strands of research have …
A review of fake news detection approaches: A critical analysis of relevant studies and highlighting key challenges associated with the dataset, feature representation …
Currently, social networks have become the main source to acquire news about current
global affairs. However, fake news appears and spreads on social media daily. This …
global affairs. However, fake news appears and spreads on social media daily. This …
Detecting rumors on social media based on a CNN deep learning technique
A Alsaeedi, M Al-Sarem - Arabian Journal for Science and Engineering, 2020 - Springer
Currently, it is easy to create content and share it via social media platforms such as Twitter,
Facebook, and Sina Weibo. However, some problems can occur when the shared content …
Facebook, and Sina Weibo. However, some problems can occur when the shared content …
Rumor detection in social network based on user, content and lexical features
Emergence in the social network leads to the extensive and faster diffusion of news than
conventional news channels. Verification of data is challenging due to massive information …
conventional news channels. Verification of data is challenging due to massive information …
[PDF][PDF] Arabic Fake News Detection Using Deep Learning.
Nowadays, an unprecedented number of users interact through social media platforms and
generate a massive amount of content due to the explosion of online communication …
generate a massive amount of content due to the explosion of online communication …