YOLOv5-ACS: Improved Model for Apple Detection and Positioning in Apple Forests in Complex Scenes
Apple orchards, as an important center of economic activity in forestry special crops, can achieve yield prediction and automated harvesting by detecting and locating apples. Small apples, occlusion, dim lighting at night, blurriness, cluttered backgrounds, and other complex scenes significantly aff...
Main Authors: | Jianping Liu, Chenyang Wang, Jialu Xing |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-11-01
|
Series: | Forests |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4907/14/12/2304 |
Similar Items
-
An improved YOLOv5s model for assessing apple graspability in automated harvesting scene
by: Huibin Li, et al.
Published: (2023-12-01) -
Establishment of apple as an appealing cash crop in Sri Lanka: need, challenges, and opportunities
by: W. M. D. A. Wijesundara, et al.
Published: (2020-12-01) -
The best of apples/
by: David, Madeleine
Published: (1990) -
Distribution of Apple stem grooving virus in apple trees in the Czech Republic
by: Jaroslav Polák, et al.
Published: (2001-03-01) -
Real-Time Detection of Apple Leaf Diseases in Natural Scenes Based on YOLOv5
by: Huishan Li, et al.
Published: (2023-04-01)