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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:

Deep learning-empowered crop breeding: intelligent, efficient and promising
Xiaoding Wang, Haitao Zeng, Limei Lin, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 13

Showing 13 citing articles:

Remote sensing revolutionizing agriculture: Toward a new frontier
Xiaoding Wang, Haitao Zeng, Xu Yang, et al.
Future Generation Computer Systems (2025) Vol. 166, pp. 107691-107691
Closed Access | Times Cited: 1
Developing new sugarcane varieties suitable for mechanized production in China: principles, strategies and prospects
Youxiong Que, Qibin Wu, Hua Zhang, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 9
Fed-MPS: Federated learning with local differential privacy using model parameter selection for resource-constrained CPS
Shui Jiang, Xiaoding Wang, Youxiong Que, et al.
Journal of Systems Architecture (2024) Vol. 150, pp. 103108-103108
Closed Access | Times Cited: 4
Development of Machine Learning Methods for Accurate Prediction of Plant Disease Resistance
Qi Liu, Shimin Zuo, Shasha Peng, et al.
Engineering (2024) Vol. 40, pp. 100-110
Open Access | Times Cited: 3
AI and the next medical revolution: deep learning's uncharted healthcare promise
L B Krithika, S. Vishnu, Evans Kotei, et al.
Engineering Research Express (2024) Vol. 6, Iss. 2, pp. 022202-022202
Closed Access | Times Cited: 2
Computer-Aided Crop Yield Forecasting Techniques - Systematic Review Highlighting the Application of AI
Raji Pushpalatha, Thendiyath Roshni, G. Byju, et al.
Environmental Modeling & Assessment (2024) Vol. 29, Iss. 6, pp. 1095-1110
Closed Access | Times Cited: 1
Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models
Ithiphat Opasatian, Tofael Ahamed
AgriEngineering (2024) Vol. 6, Iss. 3, pp. 3408-3426
Open Access | Times Cited: 1
Automatic plant phenotyping analysis of Melon (Cucumis melo L.) germplasm resources using deep learning methods and computer vision
Shan Xu, Jia Shen, Yuzhen Wei, et al.
Plant Methods (2024) Vol. 20, Iss. 1
Closed Access | Times Cited: 1
Harnessing AI-Powered Genomic Research for Sustainable Crop Improvement
Elżbieta Wójcik‐Gront, Bartłomiej Zieniuk, Magdalena Pawełkowicz
Agriculture (2024) Vol. 14, Iss. 12, pp. 2299-2299
Open Access | Times Cited: 1
High-throughput plant phenotyping analysis of Melon (Cucumis melo L.) germplasm resources using deep learning methods and computer vision
Shan Xu, Jia Shen, Yuzhen Wei, et al.
Research Square (Research Square) (2024)
Open Access
Advancing plant biology through deep learning-powered natural language processing
Shuang Peng, Loïc Rajjou
Plant Cell Reports (2024) Vol. 43, Iss. 8
Closed Access
Intelligent technologies and their transformative role in modern agriculture: A comparative approach
Karishma Behera, Anita Babbar, R. G. Vyshnavi, et al.
Environment Conservation Journal (2024) Vol. 25, Iss. 3, pp. 870-880
Open Access
The use of artificial intelligence in the production of genetically modified (GM) crops: a recent promising strategy for enhancing the acceptability of GM products ?
Gideon Sadikiel Mmbando
Deleted Journal (2024) Vol. 6, Iss. 11
Open Access
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