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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:

Predicting soluble solids content in “Fuji” apples of different ripening stages based on multiple information fusion
Yirui Huang, Juan Wang, Na Li, et al.
Pattern Recognition Letters (2021) Vol. 151, pp. 76-84
Closed Access | Times Cited: 11

Showing 11 citing articles:

Applications of machine learning techniques for enhancing nondestructive food quality and safety detection
Yuandong Lin, Ji Ma, Qijun Wang, et al.
Critical Reviews in Food Science and Nutrition (2022) Vol. 63, Iss. 12, pp. 1649-1669
Closed Access | Times Cited: 99
Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
Salvador Castillo‐Gironés, Sandra Munera, Marcelino Martı́nez-Sober, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109938-109938
Open Access | Times Cited: 4
Application and Prospects of Artificial Intelligence (AI)-Based Technologies in Fruit Production Systems
Sudip Kumar Dutta, Birshika Bhutia, Tanuj Misra, et al.
Deleted Journal (2025) Vol. 67, Iss. 1
Closed Access | Times Cited: 2
Integrating deep learning and data fusion for enhanced oranges soluble solids content prediction using machine vision and Vis/NIR spectroscopy
Zhizhong Sun, Hao Tian, Dong Hu, et al.
Food Chemistry (2024) Vol. 464, pp. 141488-141488
Closed Access | Times Cited: 6
Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology
Ting Tang, Qing Luo, Yang Liu, et al.
Foods (2023) Vol. 13, Iss. 1, pp. 25-25
Open Access | Times Cited: 10
Prediction of the Maturity of Greenhouse Grapes Based on Imaging Technology
Xinguang Wei, Linlin Wu, Dong Ge, et al.
Plant Phenomics (2022) Vol. 2022
Open Access | Times Cited: 16
Prediction of apple moisture content based on hyperspectral imaging combined with neural network modeling
Yue-Yue Chen, Shuiping Li, Xiaobo Zhang, et al.
Scientia Horticulturae (2024) Vol. 338, pp. 113739-113739
Closed Access | Times Cited: 2
NIR Inversion Model of Larch Wood Density at Different Moisture Contents Based on MVO-BPNN
Zhiyuan Wang, Zheyu Zhang, Roger A. Williams, et al.
Journal of Applied Spectroscopy (2024) Vol. 91, Iss. 2, pp. 472-479
Closed Access | Times Cited: 1
Editorial paper for pattern recognition letters VSI on multi-view representation learning and multi-modal information representation
Dan Song, Wenshu Zhang, Tongwei Ren, et al.
Pattern Recognition Letters (2022) Vol. 159, pp. 165-166
Closed Access | Times Cited: 3
Feature Normalization Reweighting Regression Network for Sugar Content Measurement of Grapes
Mei Jia, Jiuliang Li, Tianyang Hu, et al.
Applied Sciences (2022) Vol. 12, Iss. 15, pp. 7474-7474
Open Access | Times Cited: 3
Predictive modeling of patulin accumulation in apple lesions infected by Penicillium expansum using machine learning
Xiaoyan Cheng, Rongxia Li, Pengdong Xie, et al.
Postharvest Biology and Technology (2024) Vol. 217, pp. 113115-113115
Closed Access
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