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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 accurately predicts food categories and nutrients based on ingredient statements
Peihua Ma, Zhikun Zhang, Ying Li, et al.
Food Chemistry (2022) Vol. 391, pp. 133243-133243
Open Access | Times Cited: 20

Showing 20 citing articles:

A step forward in food science, technology and industry using artificial intelligence
Rezvan Esmaeily, Mohammad Amin Razavi, Seyed Hadi Razavi
Trends in Food Science & Technology (2023) Vol. 143, pp. 104286-104286
Closed Access | Times Cited: 29
Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism
Rahib H. Abiyev, Joseph A Adepoju
Human-Centric Intelligent Systems (2024) Vol. 4, Iss. 1, pp. 171-186
Open Access | Times Cited: 11
Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review
Ali Haider, Shahzad Zafar Iqbal, Ijaz Ahmad Bhatti, et al.
Comprehensive Reviews in Food Science and Food Safety (2024) Vol. 23, Iss. 3
Closed Access | Times Cited: 10
Emerging technologies for preservation and quality evaluation of postharvest edible mushrooms: A review
Rongrong Xia, Zhenshan Hou, Heran Xu, et al.
Critical Reviews in Food Science and Nutrition (2023) Vol. 64, Iss. 23, pp. 8445-8463
Closed Access | Times Cited: 18
Review of deep learning-based methods for non-destructive evaluation of agricultural products
Zhenye Li, Dongyi Wang, Tingting Zhu, et al.
Biosystems Engineering (2024) Vol. 245, pp. 56-83
Closed Access | Times Cited: 5
A cumulative learning method for pixel-level Hyperspectral detection of aflatoxins on peanuts using convolutional neural network
Yifan Zhao, Hongfei Zhu, Limiao Deng, et al.
Journal of Food Composition and Analysis (2025), pp. 107356-107356
Closed Access
Revolutionizing Food Safety in the Airline Industry: AI-Powered Smart Solutions
Nida Kanwal, Min Zhang, Mustafa Zeb, et al.
Trends in Food Science & Technology (2025), pp. 104970-104970
Closed Access
Neural network in food analytics
Peihua Ma, Zhikun Zhang, Xiaoxue Jia, et al.
Critical Reviews in Food Science and Nutrition (2022) Vol. 64, Iss. 13, pp. 4059-4077
Closed Access | Times Cited: 25
Deep Learning-Based Near-Infrared Hyperspectral Imaging for Food Nutrition Estimation
Tianhao Li, Wensong Wei, Shujuan Xing, et al.
Foods (2023) Vol. 12, Iss. 17, pp. 3145-3145
Open Access | Times Cited: 14
Few-shot entity linking of food names
Darius Feher, Faridz Ibrahim, Zhuyan Cheng, et al.
Information Processing & Management (2023) Vol. 60, Iss. 5, pp. 103463-103463
Open Access | Times Cited: 5
Aptamer recognition-promoted specific intercalation of iridium complexes in G-quadruplex DNA for label-free and enzyme-free phosphorescence analysis of kanamycin
Hongjie Qi, Lixin Feng, Suixin Zhao, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2022) Vol. 284, pp. 121758-121758
Closed Access | Times Cited: 6
Research Use of the IRI Marketing Data Set: Bibliography
Michael W. Kruger
SSRN Electronic Journal (2013)
Closed Access | Times Cited: 5
Computational screening for new neuroprotective ingredients against Alzheimer's disease from bilberry by cheminformatics approaches
Ran Xiao, Rui Liang, Yunhui Cai, et al.
Frontiers in Nutrition (2022) Vol. 9
Open Access | Times Cited: 3
Using deep learning model to predict micronutrients in food after processing
Hoang Vu Nguyen, Ngoc Bich Dao, Hương Thanh Trần, et al.
Ministry of Science and Technology Vietnam (2024) Vol. 66, Iss. 6, pp. 1-8
Open Access
AI Advancements in Food, Nutrition and Dietetics: A Comprehensive Survey
V. M. Kulkarni, Samarth Lawate, Bhagat Singh Jaiswal, et al.
Lecture notes in networks and systems (2024), pp. 304-318
Closed Access
Prediction of Physico-chemical Properties in Tomatoes Using Deep Neural Architecture
Ninja Begum, Manuj Kumar Hazarika
Agricultural Research (2024)
Closed Access
Machine learning accurately predicts food exchange list and the exchangeable portion
David Jovani Hernández-Hernández, Ana Bertha Pérez‐Lizaur, Berenice Palacios‐González, et al.
Frontiers in Nutrition (2023) Vol. 10
Open Access | Times Cited: 1
SOOTYDEEPFIC: Food Item Classification Using Sooty Tern optimized Deep Learning Network

International journal of intelligent engineering and systems (2023) Vol. 17, Iss. 1, pp. 783-793
Open Access | Times Cited: 1
Predicting health effects of food compounds via ensemble machine learning
Suyu Mei
Research Square (Research Square) (2023)
Open Access
Food composition data: can we take it for granted? : Quality considerations in the production and use of food composition data
Susanne Westenbrink
(2023)
Open Access
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