Real-Time Detection for Wheat Head Applying Deep Neural Network
Wheat head detection can estimate various wheat traits, such as density, health, and the presence of wheat head. However, traditional detection methods have a huge array of problems, including low efficiency, strong subjectivity, and poor accuracy. In this paper, a method of wheat-head detection bas...
Main Authors: | Bo Gong, Daji Ergu, Ying Cai, Bo Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-12-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/1/191 |
Similar Items
-
WDN: A One-Stage Detection Network for Wheat Heads with High Performance
by: Pengshuo Sun, et al.
Published: (2022-03-01) -
WheatLFANet: in-field detection and counting of wheat heads with high-real-time global regression network
by: Jianxiong Ye, et al.
Published: (2023-10-01) -
Wheat Teacher: A One-Stage Anchor-Based Semi-Supervised Wheat Head Detector Utilizing Pseudo-Labeling and Consistency Regularization Methods
by: Rui Zhang, et al.
Published: (2024-02-01) -
Detecting Wheat Heads from UAV Low-Altitude Remote Sensing Images Using Deep Learning Based on Transformer
by: Jiangpeng Zhu, et al.
Published: (2022-10-01) -
Fusarium spp. In wheat grain in the Czech Republic analysed by PCR method
by: Jan Nedělník, et al.
Published: (2007-12-01)