CRE-YOLO: Efficient Jaboticaba Tree Detection on UAV Platforms
This study focuses on the detection of Jaboticaba trees in an orchard located in Nanxiong City, Guangdong Province, utilizing UAV platforms to enhance precision agriculture practices. The primary objective is to compress the parameters of deep learning models while improving accuracy to enable their...
Saved in:
Main Authors: | Junyu Huang, Renbo Luo, Yuna Tan, Zhuowen Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10807194/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing palm precision agriculture: An approach based on deep learning and UAVs for efficient palm tree detection
by: Yosra Hajjaji, et al.
Published: (2025-03-01) -
DFTD-YOLO: Lightweight Multi-Target Detection From Unmanned Aerial Vehicle Viewpoints
by: Yuteng Chen, et al.
Published: (2025-01-01) -
SED-YOLO based multi-scale attention for small object detection in remote sensing
by: Xiaotan Wei, et al.
Published: (2025-01-01) -
SMC-YOLO: A High-Precision Maize Insect Pest-Detection Method
by: Qinghao Wang, et al.
Published: (2025-01-01) -
Estudo das características da produção, comercialização e qualidade de produtos derivados de jabuticaba no município de Sabará-Minas Gerais, Brasil.
by: Nathália Andrade NEVES, et al.
Published: (2020-05-01)