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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:

Hybrid deep learning techniques for estimation of daily crop evapotranspiration using limited climate data
Gitika Sharma, Ashima Singh, Sushma Jain
Computers and Electronics in Agriculture (2022) Vol. 202, pp. 107338-107338
Closed Access | Times Cited: 19

Showing 19 citing articles:

A review of deep learning techniques used in agriculture
Ishana Attri, Lalit Kumar Awasthi, Teek Parval Sharma, et al.
Ecological Informatics (2023) Vol. 77, pp. 102217-102217
Closed Access | Times Cited: 124
Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study
Hussam Eldin Elzain, Osman Abdalla, Mohammed Abdallah, et al.
Journal of Environmental Management (2024) Vol. 354, pp. 120246-120246
Closed Access | Times Cited: 17
Exploring interpretable and non-interpretable machine learning models for estimating winter wheat evapotranspiration using particle swarm optimization with limited climatic data
Xin Zhao, Lei Zhang, Ge Zhu, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108140-108140
Closed Access | Times Cited: 17
Temperature forecasting of grain in storage: A multi-output and spatiotemporal approach based on deep learning
Zhongke Qu, Yang Zhang, Chao Hong, et al.
Computers and Electronics in Agriculture (2023) Vol. 208, pp. 107785-107785
Closed Access | Times Cited: 14
Predição de temperatura ambiente por meio de rede neural artificial aplicada à sistemas de aeração de grãos
Oséas Machado Gomes, Manuel Osório Binelo, Márcia de F. B. Binelo, et al.
Proceeding Series of the Brazilian Society of Computational and Applied Mathematics (2025)
Closed Access
Comprehensive analysis of methods for estimating actual paddy evapotranspiration—A review
Kiran Bala Behura, S. K. Raul, Jagadish Chandra Paul, et al.
Frontiers in Water (2025) Vol. 7
Open Access
LandBench 1.0: A benchmark dataset and evaluation metrics for data-driven land surface variables prediction
Qingliang Li, Cheng Zhang, Wei Shangguan, et al.
Expert Systems with Applications (2023) Vol. 243, pp. 122917-122917
Open Access | Times Cited: 10
Evapotranspiration, water use efficiency, and yield for film mulched maize under different nitrogen-fertilization rates and climate conditions
Heng Fang, Yuannong Li, Xiaobo Gu, et al.
Agricultural Water Management (2024) Vol. 301, pp. 108935-108935
Open Access | Times Cited: 3
Estimating soil mineral nitrogen from data-sparse field experiments using crop model-guided deep learning approach
Rishabh Gupta, Satya Krishna Pothapragada, Weihuang Xu, et al.
Computers and Electronics in Agriculture (2024) Vol. 225, pp. 109355-109355
Closed Access | Times Cited: 3
Prediction of Large-Scale Regional Evapotranspiration Based on Multi-Scale Feature Extraction and Multi-Headed Self-Attention
Xin Zheng, Sha Zhang, Jiahua Zhang, et al.
Remote Sensing (2024) Vol. 16, Iss. 7, pp. 1235-1235
Open Access | Times Cited: 1
A Novel Hybrid Deep Learning Framework for Evaluating Field Evapotranspiration Considering the Impact of Soil Salinity
Yao Rong, Weishu Wang, Peijin Wu, et al.
Water Resources Research (2024) Vol. 60, Iss. 9
Open Access | Times Cited: 1
Design of Farm Irrigation Control System Based on the Composite Controller
Xue Li, Zhiqiang Li, Dongbo Xie, et al.
Actuators (2023) Vol. 12, Iss. 2, pp. 81-81
Open Access | Times Cited: 4
Temperature Forecasting of Grain in Storage: An Improved Approach Based on Broad Learning Network
Qifu Wang, Minglei Hou, Yao Qin, et al.
IEEE Access (2024) Vol. 12, pp. 115112-115123
Open Access
Internet of Things-Enabled Irrigation Management System for Precision Agriculture
Siddharam, L. Aiswarya, Venkatesh Gaddikeri, et al.
Advances in geographical and environmental sciences (2024), pp. 231-250
Closed Access
Interpolation of Environmental Data Using Deep Learning and Model Inference
Chibuike Chiedozie Ibebuchi, Itohan‐Osa Abu
Machine Learning Science and Technology (2024) Vol. 5, Iss. 2, pp. 025046-025046
Open Access
Evaluation of crop water stress index of wheat by using machine learning models
Aditi Yadav, Likith Muni Narakala, Hitesh Upreti, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 10
Closed Access
Estimating actual crop evapotranspiration by using satellite images coupled with hybrid deep learning-based models in potato fields
Larona Keabetswe, Yiyin He, Chao Li, et al.
Agricultural Water Management (2024) Vol. 306, pp. 109191-109191
Open Access
Estimating and forecasting daily reference crop evapotranspiration in China with temperature-driven deep learning models
Jia Zhang, Yimin Ding, Lei Zhu, et al.
Agricultural Water Management (2024) Vol. 307, pp. 109268-109268
Open Access
Interpretable Approaches to Predict Evapotranspiration
Muhammad Uzair, Stefania Tomasiello, Evelin Loit
Lecture notes in networks and systems (2023), pp. 275-284
Closed Access | Times Cited: 1
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