Research on efficient detection network method for remote sensing images based on self attention mechanism
Authors:
- Jing LiJLJing Li
- XiaoMeng WeiXWXiaoMeng Wei
- 17 December 2023
- journal article
- research article
- Published by Elsevier in Image and Vision Computing
- Vol. 142
Abstract
No abstract availableKeywords
Funding Information
- National Science Foundation
This publication has 12 references indexed in Scilit:
- FESSD:SSD target detection based on feature fusion and feature enhancementJournal of Real-Time Image Processing, 2023
- YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systemsComputers and Electronics in Agriculture, 2023
- UAV remote sensing detection of tea leaf blight based on DDMA-YOLOComputers and Electronics in Agriculture, 2023
- YOLO-Extract: Improved YOLOv5 for Aircraft Object Detection in Remote Sensing ImagesIEEE Access, 2023
- Generalized few-shot object detection in remote sensing imagesISPRS Journal of Photogrammetry and Remote Sensing, 2022
- Detection of maize tassels for UAV remote sensing image with an improved YOLOX ModelJournal of Integrative Agriculture, 2022
- Precursors to large rockslides visible on optical remote-sensing images and their implications for landslide early detectionLandslides, 2022
- Object detection using YOLO: challenges, architectural successors, datasets and applicationsMultimedia Tools and Applications, 2022
- Selective kernel convolution deep residual network based on channel-spatial attention mechanism and feature fusion for mechanical fault diagnosisISA Transactions, 2022
- MS-SSD: multi-scale single shot detector for ship detection in remote sensing imagesApplied Intelligence, 2022