Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Explainable artificial intelligence and interpretable machine learning for agricultural data analysis
Masahiro Ryo
Artificial Intelligence in Agriculture (2022) Vol. 6, pp. 257-265
Open Access | Times Cited: 65

Showing 26-50 of 65 citing articles:

Transdisciplinary coordination is essential for advancing agricultural modeling with machine learning
Lily‐belle Sweet, Ioannis N. Athanasiadis, Ron van Bree, et al.
One Earth (2025) Vol. 8, Iss. 4, pp. 101233-101233
Open Access
An interpretable temperature prediction method for grain in storage based on improved temporal Fusion Transformers
Xinze Li, Wenfu Wu, Hongpeng Guo, et al.
Computers and Electronics in Agriculture (2025) Vol. 236, pp. 110414-110414
Closed Access
Digitalization in AgriEngineering 5.0
Serra Aksoy, Pınar Demircioğlu, İsmail Böğrekçi, et al.
Lecture notes in mechanical engineering (2025), pp. 449-462
Closed Access
An Explainable AI Approach to Agrotechnical Monitoring and Crop Diseases Prediction in Dnipro Region of Ukraine
Іvan Laktionov, Grygorii Diachenko, Danuta Rutkowska, et al.
Journal of Artificial Intelligence and Soft Computing Research (2023) Vol. 13, Iss. 4, pp. 247-272
Open Access | Times Cited: 10
Tree-Based Modeling for Large-Scale Management in Agriculture: Explaining Organic Matter Content in Soil
W.O. Lee, Juhwan Lee
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 1811-1811
Open Access | Times Cited: 3
Higher crop rotational diversity in more simplified agricultural landscapes in Northeastern Germany
Josepha Schiller, Clemens Jänicke, Moritz Reckling, et al.
Landscape Ecology (2024) Vol. 39, Iss. 4
Open Access | Times Cited: 3
Advancing agriculture with machine learning: a new frontier in weed management
Mohammad Mehdizadeh, Duraid K. A. Al-Taey, Anahita Omidi, et al.
Frontiers of Agricultural Science and Engineering (2024)
Open Access | Times Cited: 3
The CropGPT project: Call for a global, coordinated effort in precision design breeding driven by AI using biological big data
Wanchao Zhu, Rui Han, Xiaoyang Shang, et al.
Molecular Plant (2023) Vol. 17, Iss. 2, pp. 215-218
Open Access | Times Cited: 9
Modelling the potential for local management practices to offset climate change impacts on freshwater macroinvertebrate communities
James Orr, Gianbattista Bussi, Jocelyne Hughes, et al.
Freshwater Biology (2024) Vol. 69, Iss. 3, pp. 435-449
Open Access | Times Cited: 2
Tree-based Modeling for Large-scale Management in Agriculture: Explaining Organic Matter Content in Soil
W.O. Lee, Juhwan Lee
(2024)
Open Access | Times Cited: 2
The Use of Interpretable Artificial Intelligence Inferences in the Estimation of Optimal Moisture Content Utilizing Basic Soil Parameters
Rodney Ewusi-Wilson, Jerome Anabannye Yendaw, Sylvanus Sebbeh-Newton, et al.
Indian geotechnical journal (2024)
Closed Access | Times Cited: 2
Explainable AI (EXAI) for Smart Healthcare Automation
Wasswa Shafik, D. Lakshmi
Advances in bioinformatics and biomedical engineering book series (2024), pp. 289-316
Closed Access | Times Cited: 2
On the Black-box Explainability of Object Detection Models for Safe and Trustworthy Industrial Applications
Alain Andrés, Aitor Martínez-Seras, Ibai Laña, et al.
Results in Engineering (2024), pp. 103498-103498
Open Access | Times Cited: 2
Machine Learning-Enabled Internet of Things Solution for Smart Agriculture Operations
Palanivel Kuppusamy, Joseph K. Suresh, Suganthi Shanmugananthan
Advances in systems analysis, software engineering, and high performance computing book series (2023), pp. 84-115
Closed Access | Times Cited: 4
ODL Net: Object detection and location network for small pears around the thinning period
Yuqi Lu, Shuang Du, Ze Ji, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108115-108115
Open Access | Times Cited: 4
Explainability and Interpretability Concepts for Edge AI Systems
Ovidiu Vermesan, Vincenzo Piuri, Fabio Scotti, et al.
River Publishers eBooks (2024), pp. 197-227
Open Access | Times Cited: 1
Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model
Mohamed Bouni, Badr Hssina, Khadija Douzi, et al.
Journal of Electrical and Computer Engineering (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 1
Decoding the spatial dynamics of sales and rental prices in a high-pressure Portuguese housing market: A random forest approach for the Lisbon Metropolitan Area
Miguel Leal, Marina Carreiras, Sónia Alves
Cities (2024) Vol. 158, pp. 105631-105631
Open Access | Times Cited: 1
TRMM-era neural networks for GPM-era satellite quantitative precipitation estimation (QPE)
Livia J. Leganés, Andrés Navarro, GyuWon Lee, et al.
Atmospheric Research (2024), pp. 107879-107879
Closed Access | Times Cited: 1
An Explainable AI (XAI)-Based Framework for Detecting Diseases in Paddy Crops
Lohith Sowmiyan, Sairam Vaidya, G. R. Karpagam
Lecture notes in networks and systems (2024), pp. 411-430
Closed Access
Advancing Edge Artificial Intelligence
Ovidiu Vermesan, Dave Marples
River Publishers eBooks (2024)
Open Access
Impact of novel methods and research approaches in plant pathology: Are individual advances sufficient to meet the wider challenges of disease management?
Michael Jeger, R.M. Beresford, Anna Berlin, et al.
Plant Pathology (2024) Vol. 73, Iss. 7, pp. 1629-1655
Closed Access
Credit Card Fraud Detection with XAI: Improving Interpretability and Trust
Bohdan Vihurskyi
(2024) Vol. 2, pp. 1-6
Closed Access
Interpretation of Glaciers Mass Change within the Upper Yukon Watershed from Grace Using Explainable Automated Machine Learning Algorithms
Cheick Doumbia, Alain N. Rousseau, Hakan Başağaoğlu, et al.
(2024)
Closed Access
Leveraging Incremental Decision Trees and In-Vivo Biosensors for an Explainable Plant Health Monitoring System
Giovanni Panella, Pietro Ducange, Manuele Bettelli, et al.
(2024), pp. 1-8
Closed Access

Scroll to top