Remote sensing scene classification via multi-stage self-guided separation network

J Wang, W Li, M Zhang, R Tao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In recent years, remote-sensing scene classification is one of the research hotspots and has
played an important role in the field of intelligent interpretation of remote-sensing data …

Large kernel sparse ConvNet weighted by multi-frequency attention for remote sensing scene understanding

J Wang, W Li, M Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Remote sensing scene understanding is a highly challenging task, and has gradually
emerged as a research hotspot in the field of intelligent interpretation of remote sensing …

Transferring CNN with adaptive learning for remote sensing scene classification

W Wang, Y Chen, P Ghamisi - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Accurate classification of remote sensing (RS) images is a perennial topic of interest in the
RS community. Recently, transfer learning, especially for fine-tuning pretrained …

Fcihmrt: Feature cross-layer interaction hybrid method based on res2net and transformer for remote sensing scene classification

Y Huo, S Gang, C Guan - Electronics, 2023 - mdpi.com
Scene classification is one of the areas of remote sensing image processing that is gaining
much attention. Aiming to solve the problem of the limited precision of optical scene …

Unmanned aerial vehicle perspective small target recognition algorithm based on improved yolov5

H Xu, W Zheng, F Liu, P Li, R Wang - Remote Sensing, 2023 - mdpi.com
Small target detection has been widely used in applications that are relevant to everyday life
and have many real-time requirements, such as road patrols and security surveillance …

Multimodal information fusion for weather systems and clouds identification from satellite images

C Bai, D Zhao, M Zhang, J Zhang - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Seeing the cloud and then understanding the weather is one of the important means for
people to forecast weather. There has been a certain progress in the use of deep learning …

Harvesting the Landsat archive for land cover land use classification using deep neural networks: Comparison with traditional classifiers and multi-sensor benefits

G Mountrakis, SS Heydari - ISPRS Journal of Photogrammetry and Remote …, 2023 - Elsevier
The Landsat archive, with a multi-decadal global coverage is a prime candidate for deep
learning classification methods due to the large data volume. Local studies have evaluated …

EFCOMFF-Net: A multiscale feature fusion architecture with enhanced feature correlation for remote sensing image scene classification

J Chen, J Yi, A Chen, Z ** - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Remote sensing images have the essential attribute of large-scale spatial variation and
complex scene information, as well as the high similarity between various classes and the …

Hierarchical multiscale dense networks for intelligent fault diagnosis of electromechanical systems

Y Xu, X Yan, B Sun, Z Liu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Deep learning, which is characterized by its powerful feature extraction capabilities, has
been widely used in the field of mechanical fault diagnosis. Traditional deep learning …

[HTML][HTML] Urban vegetation extraction from high-resolution remote sensing imagery on SD-UNet and vegetation spectral features

N Lin, H Quan, J He, S Li, M **ao, B Wang, T Chen… - Remote Sensing, 2023 - mdpi.com
Urban vegetation plays a crucial role in the urban ecological system. Efficient and accurate
extraction of urban vegetation information has been a pressing task. Although the …