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Remote-sensing scene classification via multistage self-guided separation network
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 …
played an important role in the field of intelligent interpretation of remote-sensing data …
Transferring CNN with adaptive learning for remote sensing scene classification
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 …
RS community. Recently, transfer learning, especially for fine-tuning pretrained …
Large kernel sparse ConvNet weighted by multi-frequency attention for remote sensing scene understanding
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 …
emerged as a research hotspot in the field of intelligent interpretation of remote sensing …
[HTML][HTML] 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 …
much attention. Aiming to solve the problem of the limited precision of optical scene …
[HTML][HTML] Unmanned aerial vehicle perspective small target recognition algorithm based on improved yolov5
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 …
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
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 …
people to forecast weather. There has been a certain progress in the use of deep learning …
EFCOMFF-Net: A multiscale feature fusion architecture with enhanced feature correlation for remote sensing image scene classification
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 …
complex scene information, as well as the high similarity between various classes and the …
Harvesting the Landsat archive for land cover land use classification using deep neural networks: Comparison with traditional classifiers and multi-sensor benefits
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 …
learning classification methods due to the large data volume. Local studies have evaluated …
[HTML][HTML] Urban vegetation extraction from high-resolution remote sensing imagery on SD-UNet and vegetation spectral features
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 …
extraction of urban vegetation information has been a pressing task. Although the …
Hierarchical multiscale dense networks for intelligent fault diagnosis of electromechanical systems
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 …
been widely used in the field of mechanical fault diagnosis. Traditional deep learning …