Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
LungNet: A hybrid deep-CNN model for lung cancer diagnosis using CT and wearable sensor-based medical IoT data
Lung cancer, also known as pulmonary cancer, is one of the deadliest cancers, but yet
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
curable if detected at the early stage. At present, the ambiguous features of the lung cancer …
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 …
An efficient approach based on privacy-preserving deep learning for satellite image classification
Satellite images have drawn increasing interest from a wide variety of users, including
business and government, ever since their increased usage in important fields ranging from …
business and government, ever since their increased usage in important fields ranging from …
[PDF][PDF] A comprehensive review of the recent advancement in integrating deep learning with geographic information systems
A Raihan - Research Briefs on Information and Communication …, 2023 - researchgate.net
The integration of deep learning (DL) techniques with geographical information system (GIS)
offers a promising avenue for gaining novel insights into environmental phenomena by …
offers a promising avenue for gaining novel insights into environmental phenomena by …
Semantic segmentation and edge detection—Approach to road detection in very high resolution satellite images
Road detection technology plays an essential role in a variety of applications, such as urban
planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there …
planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there …
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 …
Weight initialization techniques for deep learning algorithms in remote sensing: Recent trends and future perspectives
During the last decade, several research works have focused on providing novel deep
learning methods in many application fields. However, few of them have investigated the …
learning methods in many application fields. However, few of them have investigated the …
Dual contrastive network for few-shot remote sensing image scene classification
Few-shot remote sensing image scene classification (FS-RSISC) aims at classifying remote
sensing images with only a few labeled samples. The main challenges lie in small interclass …
sensing images with only a few labeled samples. The main challenges lie in small interclass …