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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Accurate cotton diseases and pests detection in complex background based on an improved YOLOX model
Yuanjia Zhang, Benxue Ma, Yating Hu, et al.
Computers and Electronics in Agriculture (2022) Vol. 203, pp. 107484-107484
Closed Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Identification of cotton pest and disease based on CFNet- VoV-GCSP -LSKNet-YOLOv8s: a new era of precision agriculture
Rujia Li, Yiting He, Yadong Li, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 16
Cotton-YOLO: Improved YOLOV7 for rapid detection of foreign fibers in seed cotton
Qingxu Li, Wenjing Ma, Hao Li, et al.
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108752-108752
Closed Access | Times Cited: 16
DM-YOLO: improved YOLOv9 model for tomato leaf disease detection
Abudukelimu Abulizi, Junli Ye, Halidanmu Abudukelimu, et al.
Frontiers in Plant Science (2025) Vol. 15
Open Access | Times Cited: 1
Detection of Green Asparagus in Complex Environments Based on the Improved YOLOv5 Algorithm
Weiwei Hong, Zenghong Ma, Bingliang Ye, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1562-1562
Open Access | Times Cited: 25
Strawberry Detection and Ripeness Classification Using YOLOv8+ Model and Image Processing Method
Chenglin Wang, Haoming Wang, Qiyu Han, et al.
Agriculture (2024) Vol. 14, Iss. 5, pp. 751-751
Open Access | Times Cited: 13
Tomato leaf disease detection based on attention mechanism and multi-scale feature fusion
Yong Wang, P. Zhang, Shuang Tian
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 9
BerryNet-Lite: A Lightweight Convolutional Neural Network for Strawberry Disease Identification
Jianping Wang, Zhiyu Li, Guohong Gao, et al.
Agriculture (2024) Vol. 14, Iss. 5, pp. 665-665
Open Access | Times Cited: 6
Cross-comparative review of Machine learning for plant disease detection: apple, cassava, cotton and potato plants
James Daniel Omaye, Emeka Ogbuju, Grace Ataguba, et al.
Artificial Intelligence in Agriculture (2024) Vol. 12, pp. 127-151
Open Access | Times Cited: 6
A Lightweight Algorithm for Recognizing Pear Leaf Diseases in Natural Scenes Based on an Improved YOLOv5 Deep Learning Model
Jianian Li, Zhengquan Liu, Dejin Wang
Agriculture (2024) Vol. 14, Iss. 2, pp. 273-273
Open Access | Times Cited: 5
Lightweight cotton diseases real-time detection model for resource-constrained devices in natural environments
Pan Pan, Mingyue Shao, Peitong He, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 5
LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8
Haoran Feng, Xiqu Chen, Zhaoyan Duan
Agriculture (2025) Vol. 15, Iss. 4, pp. 421-421
Open Access
An Improved YOLOv8-Based Rice Pest and Disease Detection
Yang Yang, Jianlin Zhu, Haiyang Yu, et al.
Lecture notes in computer science (2025), pp. 96-107
Closed Access
A novel vegetation index for monitoring the stress levels of pest caused by dusky cotton bug
Hailin Yu, Lianbin Hu, Wenhao Cui, et al.
Computers and Electronics in Agriculture (2025) Vol. 234, pp. 110221-110221
Closed Access
A fast and lightweight detection model for wheat fusarium head blight spikes in natural environments
Chunfeng Gao, Wei Guo, Chenghai Yang, et al.
Computers and Electronics in Agriculture (2023) Vol. 216, pp. 108484-108484
Closed Access | Times Cited: 15
YOLO-EP: A detection algorithm to detect eggs of Pomacea canaliculata in rice fields
Yao Huang, Jing He, Gang Liu, et al.
Ecological Informatics (2023) Vol. 77, pp. 102211-102211
Closed Access | Times Cited: 13
A Review of the Factors Affecting Adoption of Precision Agriculture Applications in Cotton Production
Songül Gürsoy
IntechOpen eBooks (2024)
Open Access | Times Cited: 4
Assessing the Severity of Verticillium Wilt in Cotton Fields and Constructing Pesticide Application Prescription Maps Using Unmanned Aerial Vehicle (UAV) Multispectral Images
Xiaojuan Li, Zhi Liang, Guang Yang, et al.
Drones (2024) Vol. 8, Iss. 5, pp. 176-176
Open Access | Times Cited: 4
Online diagnosis platform for tomato seedling diseases in greenhouse production
Xin Jin, Xiaowu Zhu, Jiangtao Ji, et al.
International journal of agricultural and biological engineering (2024) Vol. 17, Iss. 1, pp. 80-89
Open Access | Times Cited: 3
Improving the Accuracy of Agricultural Pest Identification: Application of AEC-YOLOv8n to Large-Scale Pest Datasets
Jinfan Wei, He Gong, Shijun Li, et al.
Agronomy (2024) Vol. 14, Iss. 8, pp. 1640-1640
Open Access | Times Cited: 3
Using three-dimensional fluorescence spectroscopy and machine learning for rapid detection of adulteration in camellia oil
Yating Hu, Chaojie Wei, Xiaorong Wang, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 329, pp. 125524-125524
Closed Access | Times Cited: 3
YOLOv8-MDN-Tiny: A lightweight model for multi-scale disease detection of postharvest golden passion fruit
Dengjie Chen, Fan Lin, Caihua Lu, et al.
Postharvest Biology and Technology (2024) Vol. 219, pp. 113281-113281
Closed Access | Times Cited: 3
A Novel Crop Pest Detection Model Based on YOLOv5
Wenji Yang, Xiaoying Qiu
Agriculture (2024) Vol. 14, Iss. 2, pp. 275-275
Open Access | Times Cited: 2
Deep Learning Methods for Detecting Chilli Pests: A Novel Performance Analysis
Kantha Raju Kanaparthi, S. Sudhakar Ilango
Ecological Engineering & Environmental Technology (2024) Vol. 25, Iss. 6, pp. 234-254
Open Access | Times Cited: 2
YOLOv9-LSBN: An improved YOLOv9 model for cotton pest and disease identification method
Ruohong He, Ping Li, Jikui Zhu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Real-time field disease identification based on a lightweight model
Siyu Quan, Jiajia Wang, Zhenhong Jia, et al.
Computers and Electronics in Agriculture (2024) Vol. 226, pp. 109467-109467
Closed Access | Times Cited: 2
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