An Improved Lightweight YOLOv5 Algorithm for Detecting Strawberry Diseases

An Improved Lightweight YOLOv5 Algorithm for Detecting Strawberry Diseases

This paper proposes an improved lightweight YOLOv5 model for the real-time detection of strawberry diseases. The ghost convolution (GhostConv) module is incorporated into the YOLOv5 network, reducing the parameter numbers and floating-point operations (FLOPs) for extracting feature information using...

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Bibliographic Details
Main Authors: Shunlong Chen, Yinghua Liao, Feng Lin, Bo Huang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Computer vision
image classification
lightweight network
YOLOv5
Online Access:https://ieeexplore.ieee.org/document/10143201/

Internet

https://ieeexplore.ieee.org/document/10143201/

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