Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background

Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background

Tea disease detection is of great significance to the tea industry. In order to solve the problems such as mutual occlusion of leaves, light disturbance, and small lesion area under complex background, YOLO-SSM, a tea disease detection model, was proposed in this paper. The model introduces the SSPD...

Full description

Saved in:
Bibliographic Details
Main Authors: Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
deep learning
detection of tea diseases
convolutional neural network
target detection
leaf disease
Online Access:https://www.mdpi.com/1424-8220/25/13/4129
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items