Cucumber Flower Detection Based on YOLOv5s-SE7 Within Greenhouse Environments-Reference-Cited by-同舟云学术

Cucumber Flower Detection Based on YOLOv5s-SE7 Within Greenhouse Environments

Published:2023 Issue: Volume:11 Page:64358-64369
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Xu Xiangying¹,Wang Hongjiang¹^ORCID,Miao Minmin²,Zhang Weijian¹,Zhang Yonglong¹,Dai Haibo²,Zheng Zijian²,Zhang Xiaoxiang³

Affiliation:

1. College of Information Engineering, Yangzhou University, Yangzhou, China

2. College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China

3. Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou, Jiangsu, China

Funder

Research and Development Foundation of Jiangsu Province, China

Municipal Science and Technology Plan Project of Yangzhou

Yangzhou University Interdisciplinary Research Foundation

Natural Science Foundation of Jiangsu

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10153542.pdf?arnumber=10153542

Reference58 articles.

1. Greenhouse intelligent recognition and replanting control system based on machine vision;xiao;Proc ASABE Annu Int Meeting Amer Soc Agricult Biol Eng,2019

2. The relationship between Precision-Recall and ROC curves

3. Practical cucumber leaf disease recognition using improved Swin Transformer and small sample size

4. Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

5. Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network

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