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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:

Unsupervised and semi‐supervised learning: the next frontier in machine learning for plant systems biology
Jun Yan, Xiangfeng Wang
The Plant Journal (2022) Vol. 111, Iss. 6, pp. 1527-1538
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
Yunbi Xu, Xingping Zhang, Huihui Li, et al.
Molecular Plant (2022) Vol. 15, Iss. 11, pp. 1664-1695
Open Access | Times Cited: 159
The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management
Vijendra Kumar, Hazi Mohammad Azamathulla, Kul Vaibhav Sharma, et al.
Sustainability (2023) Vol. 15, Iss. 13, pp. 10543-10543
Open Access | Times Cited: 106
DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants
K. Wang, Muhammad Abid, Awais Rasheed, et al.
Molecular Plant (2022) Vol. 16, Iss. 1, pp. 279-293
Open Access | Times Cited: 104
3D printing of biodegradable polymers and their composites – Current state-of-the-art, properties, applications, and machine learning for potential future applications
S. A. V. Dananjaya, Venkata S. Chevali, John P. Dear, et al.
Progress in Materials Science (2024) Vol. 146, pp. 101336-101336
Open Access | Times Cited: 35
A review of artificial intelligence-assisted omics techniques in plant defense: current trends and future directions
Sneha Murmu, Dipro Sinha, Himanshushekhar Chaurasia, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 22
Drone‐based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review
Boubacar Gano, Sourav Bhadra, Justin M. Vilbig, et al.
The Plant Phenome Journal (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 20
Label-efficient learning in agriculture: A comprehensive review
Jiajia Li, Dong Chen, Xinda Qi, et al.
Computers and Electronics in Agriculture (2023) Vol. 215, pp. 108412-108412
Open Access | Times Cited: 25
Thermal imaging: The digital eye facilitates high-throughput phenotyping traits of plant growth and stress responses
Ting‐Chi Wen, Jianhong Li, Qi Wang, et al.
The Science of The Total Environment (2023) Vol. 899, pp. 165626-165626
Closed Access | Times Cited: 24
Integrative Approaches to Abiotic Stress Management in Crops: Combining Bioinformatics Educational Tools and Artificial Intelligence Applications
Xin Zhang, Zakir Ibrahim, Muhammad Bilawal Khaskheli, et al.
Sustainability (2024) Vol. 16, Iss. 17, pp. 7651-7651
Open Access | Times Cited: 11
Machine Learning-Enhanced Electrochemical Sensors for Food Safety: Applications and Perspectives
Wajeeha Pervaiz, Muhammad Afzal, Niu Feng, et al.
Trends in Food Science & Technology (2025), pp. 104872-104872
Closed Access | Times Cited: 1
Using artificial intelligence for spiritual well-being: conceptualizing predictive models
Dinesh Kumar, Enjula Uchoi
Journal of Spirituality in Mental Health (2025), pp. 1-29
Closed Access | Times Cited: 1
Application of machine learning and genomics for orphan crop improvement
Tessa R. MacNish, Monica F. Danilevicz, Philipp E. Bayer, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 1
An Outlook for Deep Learning in Ecosystem Science
George L. W. Perry, Rupert Seidl, André M. Bellvé, et al.
Ecosystems (2022) Vol. 25, Iss. 8, pp. 1700-1718
Open Access | Times Cited: 37
Machine learning for predicting phenotype from genotype and environment
Tingting Guo, Xianran Li
Current Opinion in Biotechnology (2022) Vol. 79, pp. 102853-102853
Open Access | Times Cited: 31
Semi-supervised learning and attention mechanism for weed detection in wheat
Teng Liu, Xiaojun Jin, Luyao Zhang, et al.
Crop Protection (2023) Vol. 174, pp. 106389-106389
Closed Access | Times Cited: 18
Meta‐learning shows great potential in plant disease recognition under few available samples
Xue Wu, Hongyu Deng, Qi Wang, et al.
The Plant Journal (2023) Vol. 114, Iss. 4, pp. 767-782
Open Access | Times Cited: 17
AI-powered revolution in plant sciences: advancements, applications, and challenges for sustainable agriculture and food security
Deependra Kumar Gupta, Anselmo Pagani, Paolo Zamboni, et al.
(2024) Vol. 2, Iss. 5, pp. 443-459
Open Access | Times Cited: 8
Classification of Plant Leaf Disease Recognition Based on Self-Supervised Learning
Yuzhi Wang, Yunzhen Yin, Yaoyu Li, et al.
Agronomy (2024) Vol. 14, Iss. 3, pp. 500-500
Open Access | Times Cited: 7
Spectral Intelligence: AI-Driven Hyperspectral Imaging for Agricultural and Ecosystem Applications
Faizan Ali, Ali Razzaq, Waheed Tariq, et al.
Agronomy (2024) Vol. 14, Iss. 10, pp. 2260-2260
Open Access | Times Cited: 6
Image-based classification of wheat spikes by glume pubescence using convolutional neural networks
N. V. Artemenko, М. А. Генаев, Rostislav Epifanov, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 5
Boosting of fruit choices using machine learning-based pomological recommendation system
Monica Dutta, Deepali Gupta, Sapna Juneja, et al.
SN Applied Sciences (2023) Vol. 5, Iss. 9
Open Access | Times Cited: 12
The molecular core of transcriptome responses to abiotic stress in plants: a machine learning-driven meta-analysis
Raúl Sanchez-Muñoz, Thomas Depaepe, Marketa Samalova, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
Quantum machine learning assisted lung cancer telemedicine
Alemayehu Getahun Kumela, Abebe Belay, Alemu Kebede Hordofa, et al.
AIP Advances (2023) Vol. 13, Iss. 7
Open Access | Times Cited: 11
Perspectives on the application of remote sensing technology in the cultivation of medicinal plants
Liwen Zhong, Xuemei Wu, Rong Ding, et al.
International Journal of Remote Sensing (2025), pp. 1-34
Closed Access
PhytoCluster: a generative deep learning model for clustering plant single-cell RNA-seq data
Haolin Wang, Xiangzheng Fu, Lijia Liu, et al.
aBIOTECH (2025)
Open Access
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