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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:

Estimating Yield-Related Traits Using UAV-Derived Multispectral Images to Improve Rice Grain Yield Prediction
Maria Victoria Bascon, Tomohiro Nakata, Satoshi Shibata, et al.
Agriculture (2022) Vol. 12, Iss. 8, pp. 1141-1141
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Computer vision in smart agriculture and precision farming: Techniques and applications
Sumaira Ghazal, Arslan Munir, Waqar S. Qureshi
Artificial Intelligence in Agriculture (2024) Vol. 13, pp. 64-83
Open Access | Times Cited: 37
Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models
Chandan Kumar, Partson Mubvumba, Yanbo Huang, et al.
Agronomy (2023) Vol. 13, Iss. 5, pp. 1277-1277
Open Access | Times Cited: 41
End-to-end 3D CNN for plot-scale soybean yield prediction using multitemporal UAV-based RGB images
Sourav Bhadra, Vasit Sagan, Juan Skobalski, et al.
Precision Agriculture (2023) Vol. 25, Iss. 2, pp. 834-864
Open Access | Times Cited: 23
Modern computational approaches for rice yield prediction: A systematic review of statistical and machine learning-based methods
Djavan De Clercq, Adam Mahdi
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 109852-109852
Closed Access | Times Cited: 1
Integration of Unmanned Aerial Vehicle Spectral and Textural Features for Accurate Above-Ground Biomass Estimation in Cotton
M Ingjun Chen, Caixia Yin, Tao Lin, et al.
Agronomy (2024) Vol. 14, Iss. 6, pp. 1313-1313
Open Access | Times Cited: 6
Evaluation of Sugarcane Crop Growth Monitoring Using Vegetation Indices Derived from RGB-Based UAV Images and Machine Learning Models
P. P. Ruwanpathirana, Kazuhito Sakai, Guttila Yugantha Jayasinghe, et al.
Agronomy (2024) Vol. 14, Iss. 9, pp. 2059-2059
Open Access | Times Cited: 6
Improving efficiency of ground-truth data collection for UAV-based rice growth estimation models: investigating the effect of sampling size on model accuracy
Tomoaki Yamaguchi, Kana Sasano, Keisuke Katsura
Plant Production Science (2024) Vol. 27, Iss. 1, pp. 1-13
Open Access | Times Cited: 5
Can Yield Prediction Be Fully Digitilized? A Systematic Review
Nicoleta Darra, Evangelos Anastasiou, Olga Kriezi, et al.
Agronomy (2023) Vol. 13, Iss. 9, pp. 2441-2441
Open Access | Times Cited: 13
Research on the estimation of wheat AGB at the entire growth stage based on improved convolutional features
Tao Liu, Jianliang Wang, Jiayi Wang, et al.
Journal of Integrative Agriculture (2024)
Open Access | Times Cited: 4
Ensemble of Machine Learning Algorithms for Rice Grain Yield Prediction Using UAV-Based Remote Sensing
Tapash Kumar Sarkar, Dilip Kumar Roy, Ye-Seong Kang, et al.
Journal of Biosystems Engineering (2023) Vol. 49, Iss. 1, pp. 1-19
Closed Access | Times Cited: 10
Explainable machine learning models for corn yield prediction using UAV multispectral data
Chandan Kumar, Jagmandeep Dhillon, Yanbo Huang, et al.
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 109990-109990
Open Access
Prediction of sugar beet yield and quality parameters using stacked-LSTM model with pre-harvest UAV time series data and meteorological factors
Qing Wang, Ke Shao, Zhibo Cai, et al.
Artificial Intelligence in Agriculture (2025)
Open Access
Uav Multispectral Remote Sensing Based on Xgboost for Monitoring Leaf Area Index and Aboveground Biomass of Cinnamomum Camphora
Qian Wang, Xianghui Lu, Haina Zhang, et al.
(2023)
Closed Access | Times Cited: 9
Comparison of Machine Learning Methods for Estimating Leaf Area Index and Aboveground Biomass of Cinnamomum camphora Based on UAV Multispectral Remote Sensing Data
Qian Wang, Xianghui Lu, Haina Zhang, et al.
Forests (2023) Vol. 14, Iss. 8, pp. 1688-1688
Open Access | Times Cited: 9
Improving the estimation of rice above-ground biomass based on spatio-temporal UAV imagery and phenological stages
Yan Dai, Shuang’en Yu, Tao Ma, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2
Advancements in UAV Remote Sensing for Agricultural Yield Estimation: A Systematic Comprehensive Review of Platforms, Sensors, and Data Analytics
Shubham Anil Gade, Mallappa Jadiyappa Madolli, Pedro García‐Caparrós, et al.
Remote Sensing Applications Society and Environment (2024), pp. 101418-101418
Closed Access | Times Cited: 2
A Method for Obtaining the Number of Maize Seedlings Based on the Improved YOLOv4 Lightweight Neural Network
Jiaxin Gao, Feng Tan, Jiapeng Cui, et al.
Agriculture (2022) Vol. 12, Iss. 10, pp. 1679-1679
Open Access | Times Cited: 11
Field phenotyping for African crops: overview and perspectives
Daniel Kingsley Cudjoe, Nicolas Virlet, March Castle, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 6
The Application of Unmanned Aerial Vehicles (UAVs) and Extreme Gradient Boosting (XGBoost) to Crop Yield Estimation: A Case Study of Don Tum District, Nakhon Pathom, Thailand

International Journal of Geoinformatics (2023), pp. 65-77
Open Access | Times Cited: 5
Rice Grain Detection and Counting Method Based on TCLE–YOLO Model
Yu Zou, Zefeng Tian, Jiawen Cao, et al.
Sensors (2023) Vol. 23, Iss. 22, pp. 9129-9129
Open Access | Times Cited: 5
Identification of crosstalk genes relating to ECM‐receptor interaction genes in MASH and DN using bioinformatics and machine learning
Chao Chen, Yuxi He, Ying Ni, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 6
Open Access | Times Cited: 1
Establishing a knowledge structure for yield prediction in cereal crops using unmanned aerial vehicles
Ghulam Mustafa, Y H Liu, İmran Khan, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 1
Yield Prediction Models for Rice Varieties Using UAV Multispectral Imagery in the Amazon Lowlands of Peru
Diego Goigochea-Pinchi, Maikol Justino-Pinedo, Sergio Sebastian Vega-Herrera, et al.
AgriEngineering (2024) Vol. 6, Iss. 3, pp. 2955-2969
Open Access | Times Cited: 1
Improving Efficiency of Ground-Truth Data Collection for UAV-based Rice Growth Estimation Models: Investigating the Effect of Sampling Size on Model Accuracy
Tomoaki Yamaguchi, Kana Sasano, Keisuke Katsura
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Application of RGB UAV images to identify spectral patterns and estimate rice production
Khursatul Munibah, Wahyu Iskandar, Baba Barus, et al.
Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) (2024) Vol. 52, Iss. 1, pp. 29-37
Open Access
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