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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:

Variety identification of sweet maize seeds based on hyperspectral imaging combined with deep learning
Yi Wang, Shuran Song
Infrared Physics & Technology (2023) Vol. 130, pp. 104611-104611
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Detection of chlorophyll content based on optical properties of maize leaves
Weidong Pan, Xiaodong Cheng, Rongyu Du, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 309, pp. 123843-123843
Closed Access | Times Cited: 13
Detection of Insect-Damaged Maize Seed Using Hyperspectral Imaging and Hybrid 1D-CNN-BiLSTM Model
Zheli Wang, Shuxiang Fan, Ting An, et al.
Infrared Physics & Technology (2024) Vol. 137, pp. 105208-105208
Closed Access | Times Cited: 12
Identification and Classification of Coix seed Storage Years Based on Hyperspectral Imaging Technology Combined with Deep Learning
Ruibin Bai, Zhou Jun-hui, Siman Wang, et al.
Foods (2024) Vol. 13, Iss. 3, pp. 498-498
Open Access | Times Cited: 11
DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification
Fei Pan, Dawei He, Pengjun Xiang, et al.
Agronomy (2025) Vol. 15, Iss. 1, pp. 200-200
Open Access | Times Cited: 1
Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
Salvador Castillo‐Gironés, Sandra Munera, Marcelino Martínez‐Sober, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109938-109938
Open Access | Times Cited: 1
Detection and Analysis of Chili Pepper Root Rot by Hyperspectral Imaging Technology
Yuanyuan Shao, Shengheng Ji, Guantao Xuan, et al.
Agronomy (2024) Vol. 14, Iss. 1, pp. 226-226
Open Access | Times Cited: 6
Exploring Transfer Learning for Enhanced Seed Classification: Pre-trained Xception Model
Yonis Gulzar, Zeynep Ünal, Shahnawaz Ayoub, et al.
Lecture notes in civil engineering (2024), pp. 137-147
Closed Access | Times Cited: 6
Assessment of food safety risk using machine learning-assisted hyperspectral imaging: Classification of fungal contamination levels in rice grain
Ubonrat Siripatrawan, Yoshio Makino
Microbial Risk Analysis (2024) Vol. 27-28, pp. 100295-100295
Closed Access | Times Cited: 6
An improved 3D-SwinT-CNN network to evaluate the fermentation degree of black tea
Fengle Zhu, Jian Wang, Yuqian Zhang, et al.
Food Control (2024) Vol. 167, pp. 110756-110756
Closed Access | Times Cited: 5
Applying convolutional neural networks for mustard variety recognition
Laura Slebioda, Bogna Zawieja
Euphytica (2025) Vol. 221, Iss. 2
Open Access
Application of Hyperspectral Imaging and Deep Convolutional Neural Network for Freezing Damage Identification on Embryo and Endosperm Side of Single Corn Seed
Jun Zhang, Limin Dai
Foods (2025) Vol. 14, Iss. 4, pp. 659-659
Open Access
Maize seed variety identification using hyperspectral imaging and self-supervised learning: A two-stage training approach without spectral preprocessing
Liu Zhang, Shubin Zhang, Jincun Liu, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 122113-122113
Closed Access | Times Cited: 12
Non-Destructive Classification of Maize Seeds Based on RGB and Hyperspectral Data with Improved Grey Wolf Optimization Algorithms
Chunguang Bi, Shuo Zhang, He Chen, et al.
Agronomy (2024) Vol. 14, Iss. 4, pp. 645-645
Open Access | Times Cited: 4
A maize seed variety identification method based on improving deep residual convolutional network
Jian Li, F. Xu, Shaozhong Song, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 4
Corn Seed Quality Detection Based on Spectroscopy and Its Imaging Technology: A Review
Jun Zhang, Limin Dai, Zhiwen Huang, et al.
Agriculture (2025) Vol. 15, Iss. 4, pp. 390-390
Open Access
Variety classification and identification of maize seeds based on hyperspectral imaging method
Hang Xue, Xiping Xu, Meng Xiang
Optoelectronics Letters (2025) Vol. 21, Iss. 4, pp. 234-241
Closed Access
Development of a rapid detection method for maize seed purity using a modular high-throughput near-infrared non-destructive testing system
Zheli Wang, Yaoyao Fan, Xi Tian, et al.
Infrared Physics & Technology (2025), pp. 105836-105836
Closed Access
Combination of gas chromatography-mass spectrometry and hyperspectral imaging for identification of adulterated Safflower seed oil
Zhiyong Zou, Qianlong Wang, Menghua Li, et al.
Journal of Food Composition and Analysis (2024) Vol. 135, pp. 106593-106593
Closed Access | Times Cited: 3
A method of maize seed variety identification based on near-infrared spectroscopy combined with improved DenseNet model
Haichao Zhou, Haiou Guan, Xiaodan Ma, et al.
Microchemical Journal (2024) Vol. 206, pp. 111542-111542
Closed Access | Times Cited: 3
UDATNN: A modeling scheme integrating unsupervised domain adversarial learning and tri-training strategy for variety recognition of maize seeds with domain shift
Shengqi Yan, Qibing Zhu, Min Huang, et al.
Computers and Electronics in Agriculture (2023) Vol. 213, pp. 108237-108237
Closed Access | Times Cited: 7
Efficient residual network using hyperspectral images for corn variety identification
Xueyong Li, Mingjia Zhai, Liyuan Zheng, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 2
Hyperspectral imaging combined with dual-channel deep learning feature fusion model for fast and non-destructive recognition of brew wheat varieties
Lipeng Han, Jianping Tian, Yuexiang Huang, et al.
Journal of Food Composition and Analysis (2023) Vol. 125, pp. 105785-105785
Closed Access | Times Cited: 6
Ensemble deep learning for high-precision classification of 90 rice seed varieties from hyperspectral images
AmirMasoud Taheri, Hossein Ebrahimnezhad, Mohammadhossein Sedaaghi
Journal of Ambient Intelligence and Humanized Computing (2024) Vol. 15, Iss. 6, pp. 2883-2899
Closed Access | Times Cited: 1
Rapid species discrimination of similar insects using hyperspectral imaging and lightweight edge artificial intelligence
Xuquan Wang, Zhiyuan Ma, Yujie Xing, et al.
Royal Society Open Science (2024) Vol. 11, Iss. 7
Open Access | Times Cited: 1
Identification of maize seed vigor based on hyperspectral imaging and deep learning
Peng Xu, Lixia Fu, Yongfei Pan, et al.
Bulletin of the National Research Centre/Bulletin of the National Research Center (2024) Vol. 48, Iss. 1
Open Access | Times Cited: 1
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