SAR image compressionThis paper deals with the automatic detection of Objects of Interest (OOIs) in SAR (Synthetic Aperture Radar) still images. A particular scenario in which a Light-SAR is part of the payload for HALE (High Altitude Long Endurance) platofrm, named Heliplat, currently under...
Multiscale object detection in Synthetic Aperture Radar (SAR) images can locate and recognize key objects in large-scene SAR images, and it is one of the key technologies in SAR image interpretation. However, for the simultaneous detection of SAR objects
This leads to the detection results s... H Wei,X Yu,L Shan - Mippr: Remote Sensing Image Processing, Geographic Information Systems, & Other Applications 被引量: 5发表: 2011年 Bridge Detection and Recognition in Remote Sensing SAR Images Using Pulse Coupled Neural Networks A novel double-...
Geo-spatial object detection in high-resolution satellite images has many applications in urban planning, military applications, maritime surveillance, environment control and management. Despite the success of convolutional neural networks in object detection tasks in natural images, the current deep learnin...
Sivapriya M, Suresh S (2023) Vit-dexinet: a vision transformer-based edge detection operator for small object detection in sar images. Int J Remote Sens 44(22):7057–7084 Google Scholar Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B (2021) Swin transformer: hierarch...
Deep learning has driven significant progress in object detection using Synthetic Aperture Radar (SAR) imagery. Existing methods, while achieving promising results, often struggle to effectively integrate local and global information, particularly direction-aware features. This paper proposes SAR-Net, a no...
Aiming at the problems of small target size, arbitrary target direction, and complex background in aerial image object detection using optical sensors. By using the images captured by a wild range of optical sensors such as CCD(Charge Coupled Device) and SAR(Synthetic Aperture Radar), we ...
The quantitative comparison results on the challenging NWPU VHR-10 data set, aircraft data set, Aerial-Vehicle data set and SAR-Ship data set show that our method is more accurate than existing algorithms and is effective for multi-modal remote sensing images. 展开 关键词: Object detection Deep...
2023/03 SARNetMSC MS Go Closer To See Better: Camouflaged Object Detection via Object Area Amplification and Figure-ground Conversion Haozhe Xing; Yan Wang; Xujun Wei; Hao Tang; Shuyong Gao; Wenqiang Zhang TCSVT2023 Paper/Code 2023/03 SATJS Nowhere to Disguise: Spot Camouflaged Objects via...
Feature-Transferable Pyramid Network for Dense Multi-Scale Object Detection in SAR Images In synthetic aperture radar (SAR) images, there are a large number of dense multi-scale objects, especially dense multi-scale ships docked along the coast. Existing object detection methods are difficult to sim...