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 …
Graph-based deep learning techniques for remote sensing applications: Techniques, taxonomy, and applications—A comprehensive review
In the last decade, there has been a significant surge of interest in machine learning,
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …
Finger pinching and imagination classification: A fusion of CNN architectures for IoMT-enabled BCI applications
Abstract A Brain–Computer Interface (BCI), integrated with the Internet of Medical Things
(IoMT) and based on electroencephalogram (EEG) technology, allows users to control …
(IoMT) and based on electroencephalogram (EEG) technology, allows users to control …
A hybrid privacy-preserving deep learning approach for object classification in very high-resolution satellite images
Deep learning (DL) has shown outstanding performances in many fields, including remote
sensing (RS). DL is turning into an essential tool for the RS research community. Recently …
sensing (RS). DL is turning into an essential tool for the RS research community. Recently …
Voting classifier-based intrusion detection for iot networks
Abstract Internet of Things (IoT) is transforming human lives by paving the way for the
management of physical devices on the edge. These interconnected IoT objects share data …
management of physical devices on the edge. These interconnected IoT objects share data …
An intelligent sensor based decision support system for diagnosing pulmonary ailment through standardized chest x-ray scans
Academics and the health community are paying much attention to developing smart remote
patient monitoring, sensors, and healthcare technology. For the analysis of medical scans …
patient monitoring, sensors, and healthcare technology. For the analysis of medical scans …
Improving satellite image classification accuracy using GAN-based data augmentation and vision transformers
Deep learning (DL) algorithms have shown great potential in classifying satellite imagery but
require large amounts of labeled data to make accurate predictions. However, generating …
require large amounts of labeled data to make accurate predictions. However, generating …
Incorporating big data and IoT in intelligent ecosystems: state-of-the-arts, challenges and opportunities, and future directions
The present study discusses big data (BD) and Internet of Things (IoT)-based applications in
intelligent ecosystems. The purpose of these areas is to identify important application …
intelligent ecosystems. The purpose of these areas is to identify important application …
A top-down approach for semantic segmentation of big remote sensing images
W Boulila - Earth Science Informatics, 2019 - Springer
The increasing amount of remote sensing data has opened the door to new challenging
research topics. Nowadays, significant efforts are devoted to pixel and object based …
research topics. Nowadays, significant efforts are devoted to pixel and object based …
Global outliers detection in wireless sensor networks: A novel approach integrating time‐series analysis, entropy, and random forest‐based classification.
Wireless sensor networks (WSNs) have recently attracted greater attention worldwide due to
their practicality in monitoring, communicating, and reporting specific physical phenomena …
their practicality in monitoring, communicating, and reporting specific physical phenomena …