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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:

Hyperspectral Imaging Combined With Deep Transfer Learning for Rice Disease Detection
Lei Feng, Baohua Wu, Yong He, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Automatic Recognition of Rice Leaf Diseases Using Transfer Learning
Chinna Gopi Simhadri, Hari Kishan Kondaveeti
Agronomy (2023) Vol. 13, Iss. 4, pp. 961-961
Open Access | Times Cited: 49
A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing
Luyu Shuai, Zhiyong Li, Ziao Chen, et al.
Computers and Electronics in Agriculture (2024) Vol. 217, pp. 108577-108577
Closed Access | Times Cited: 35
Plant Leaf Disease Detection, Classification, and Diagnosis Using Computer Vision and Artificial Intelligence: A Review
Anuja Bhargava, Aasheesh Shukla, Om Prakash Goswami, et al.
IEEE Access (2024) Vol. 12, pp. 37443-37469
Open Access | Times Cited: 16
Combining Random Forest and XGBoost Methods in Detecting Early and Mid-Term Winter Wheat Stripe Rust Using Canopy Level Hyperspectral Measurements
Linsheng Huang, Yong Liu, Wenjiang Huang, et al.
Agriculture (2022) Vol. 12, Iss. 1, pp. 74-74
Open Access | Times Cited: 46
Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves
Qinlin Xiao, Wentan Tang, Chu Zhang, et al.
Plant Phenomics (2022) Vol. 2022
Open Access | Times Cited: 39
Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite missions
Agata M. Wijata, M.F. Foulon, Yves Bobichon, et al.
IEEE Geoscience and Remote Sensing Magazine (2023) Vol. 11, Iss. 2, pp. 10-39
Closed Access | Times Cited: 26
Cucumber disease recognition with small samples using image-text-label-based multi-modal language model
Yiyi Cao, Lei Chen, Yuan Yuan, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 107993-107993
Closed Access | Times Cited: 23
Transfer learning in agriculture: a review
Md Ismail Hossen, Mohammad Awrangjeb, Shirui Pan, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access | Times Cited: 1
Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground”
Wu Nile, Rina Su, Na Mula, et al.
Remote Sensing (2025) Vol. 17, Iss. 4, pp. 572-572
Open Access | Times Cited: 1
The impact of high-quality data on the assessment results of visible/near-infrared hyperspectral imaging and development direction in the food fields: a review
Hongyu Xu, Jie Ren, Jidong Lin, et al.
Journal of Food Measurement & Characterization (2023) Vol. 17, Iss. 3, pp. 2988-3004
Closed Access | Times Cited: 20
A deep learning model for rapid classification of tea coal disease
Yang Xu, Yilin Mao, Li He, et al.
Plant Methods (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 19
Revolutionizing Rice Farming: Automated Identification and Classification of Rice Leaf Blight Disease Using Deep Learning
Vinay Kukreja, Rishabh Sharma, Satvik Vats
(2023), pp. 586-591
Closed Access | Times Cited: 18
Edge-Cloud Remote Sensing Data-Based Plant Disease Detection Using Deep Neural Networks With Transfer Learning
Mazin Abed Mohammed, Abdullah Lakhan, Karrar Hameed Abdulkareem, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 11219-11229
Open Access | Times Cited: 7
Plant Species Classification Based on Hyperspectral Imaging via a Lightweight Convolutional Neural Network Model
Keng-Hao Liu, Meng-Hsien Yang, Sheng-Ting Huang, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 26
Automatic Disease Detection of Basal Stem Rot Using Deep Learning and Hyperspectral Imaging
Lai Zhi Yong, Siti Khairunniza Bejo, Mahirah Jahari, et al.
Agriculture (2022) Vol. 13, Iss. 1, pp. 69-69
Open Access | Times Cited: 25
Improving chlorophyll content detection to suit maize dynamic growth effects by deep features of hyperspectral data
Ruomei Zhao, Lulu An, Weijie Tang, et al.
Field Crops Research (2023) Vol. 297, pp. 108929-108929
Closed Access | Times Cited: 15
Y–Net: Identification of Typical Diseases of Corn Leaves Using a 3D–2D Hybrid CNN Model Combined with a Hyperspectral Image Band Selection Module
Yinjiang Jia, Yaoyao Shi, Jiaqi Luo, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1494-1494
Open Access | Times Cited: 13
Development of deep and machine learning convolutional networks of variable spatial resolution for automatic detection of leaf blast disease of rice
Gagandeep Kaur, Rajni Rajni, Jagtar Singh Sivia
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109210-109210
Closed Access | Times Cited: 5
TRiP: a transfer learning based rice disease phenotype recognition platform using SENet and microservices
Peisen Yuan, Ye Xia, Yongchao Tian, et al.
Frontiers in Plant Science (2024) Vol. 14
Open Access | Times Cited: 4
DC2Net: An Asian soybean rust detection model based on hyperspectral imaging and deep learning
Jiarui Feng, Shenghui Zhang, Zhaoyu Zhai, et al.
Plant Phenomics (2024) Vol. 6
Open Access | Times Cited: 4
Hyperspectral Imaging and Machine Learning for Diagnosing Rice Bacterial Blight Symptoms Caused by Xanthomonas oryzae pv. oryzae, Pantoea ananatis and Enterobacter asburiae
Meng Zhang, Shuqi Tang, Chenjie Lin, et al.
Plants (2025) Vol. 14, Iss. 5, pp. 733-733
Open Access
Prediction of Citrus Leaf Water Content Based on Multi-Preprocessing Fusion and Improved 1-Dimensional Convolutional Neural Network
Shiqing Dou, Xuehong Ren, Xiangqian Qi, et al.
Horticulturae (2025) Vol. 11, Iss. 4, pp. 413-413
Open Access
Maize disease detection based on spectral recovery from RGB images
Jun Fu, Jindai Liu, Rongqiang Zhao, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 18
Enhancing Rice Crop Management: Disease Classification Using Convolutional Neural Networks and Mobile Application Integration
Md. Mehedi Hasan, Touficur Rahman, A. F. M. Shahab Uddin, et al.
Agriculture (2023) Vol. 13, Iss. 8, pp. 1549-1549
Open Access | Times Cited: 9
Rapid identification of the geographical origins of crops using laser-induced breakdown spectroscopy combined with transfer learning
Peng Lin, Xuelin Wen, Shixiang Ma, et al.
Spectrochimica Acta Part B Atomic Spectroscopy (2023) Vol. 206, pp. 106729-106729
Closed Access | Times Cited: 8
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