DFTD-YOLO: Lightweight Multi-Target Detection From Unmanned Aerial Vehicle Viewpoints
Due to the low detection accuracy of small and dense target objects in multi-target detection tasks from the unmanned aerial vehicle (UAV) perspective and the deployment of deep learning models for UAVs as embedded devices, these models must be lightweight. In this study, we propose an improved algo...
Saved in:
Main Authors: | Yuteng Chen, Zhaoguang Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10856002/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fusion of multi-scale attention for aerial images small-target detection model based on PARE-YOLO
by: Huiying Zhang, et al.
Published: (2025-02-01) -
A Lightweight Anti-Unmanned Aerial Vehicle Detection Method Based on Improved YOLOv11
by: Yunlong Gao, et al.
Published: (2024-12-01) -
An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique
by: Yongjun Qi, et al.
Published: (2025-01-01) -
FECI-RTDETR a Lightweight Unmanned Aerial Vehicle Infrared Small Target Detector Algorithm Based on RT-DETR
by: Renzheng Xue, et al.
Published: (2025-01-01) -
LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery
by: Van Quang Nghiem, et al.
Published: (2025-03-01)