A Multiscale Lightweight and Efficient Model Based on YOLOv7: Applied to Citrus Orchard
With the gradual increase in the annual production of citrus, the efficiency of human labor has become the bottleneck limiting production. To achieve an unmanned citrus picking technology, the detection accuracy, prediction speed, and lightweight deployment of the model are important issues. Traditi...
Main Authors: | Junyang Chen, Hui Liu, Yating Zhang, Daike Zhang, Hongkun Ouyang, Xiaoyan Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Plants |
Subjects: | |
Online Access: | https://www.mdpi.com/2223-7747/11/23/3260 |
Similar Items
-
CURI-YOLOv7: A Lightweight YOLOv7tiny Target Detector for Citrus Trees from UAV Remote Sensing Imagery Based on Embedded Device
by: Yali Zhang, et al.
Published: (2023-09-01) -
Lightweight Apple Detection in Complex Orchards Using YOLOV5-PRE
by: Lijuan Sun, et al.
Published: (2022-12-01) -
Improved YOLOv7-Tiny Complex Environment Citrus Detection Based on Lightweighting
by: Bo Gu, et al.
Published: (2023-10-01) -
YOLOv8-GABNet: An Enhanced Lightweight Network for the High-Precision Recognition of Citrus Diseases and Nutrient Deficiencies
by: Qiufang Dai, et al.
Published: (2024-11-01) -
An Accelerating Method of YOLOv7 Based on Lightweight Network Architecture
by: Jun Wang, et al.
Published: (2025-02-01)