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 …
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 …
Fusion of convolutional neural networks based on Dempster–Shafer theory for automatic pneumonia detection from chest X‐ray images
Deep learning‐based applications for disease detection are essential tools for experts to
effectively diagnose diseases at different stages. In this article, a new approach based on an …
effectively diagnose diseases at different stages. In this article, a new approach based on an …
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 …
A machine learning approach involving functional connectivity features to classify rest-EEG psychogenic non-epileptic seizures from healthy controls
Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures
(PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help …
(PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help …
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 develo** 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 …
Modeling, quality assessment, and Sobol sensitivity of water resources and distribution system in Shiraz: A probabilistic human health risk assessment
Given water's vital role in supporting life and ecosystems, global climate change and human
activities have significantly diminished its availability and quality. This study explores the …
activities have significantly diminished its availability and quality. This study explores the …
Standalone noise and anomaly detection in wireless sensor networks: a novel time‐series and adaptive Bayesian‐network‐based approach
Wireless sensor networks (WSNs) consist of small sensors with limited computational and
communication capabilities. Reading data in WSN is not always reliable due to open …
communication capabilities. Reading data in WSN is not always reliable due to open …
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 …