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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:

Novel CropdocNet Model for Automated Potato Late Blight Disease Detection from Unmanned Aerial Vehicle-Based Hyperspectral Imagery
Yue Shi, Liangxiu Han, Anthony Kleerekoper, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 396-396
Open Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques
Tej Bahadur Shahi, Cheng‐Yuan Xu, Arjun Neupane, et al.
Remote Sensing (2023) Vol. 15, Iss. 9, pp. 2450-2450
Open Access | Times Cited: 116
A survey on deep learning-based identification of plant and crop diseases from UAV-based aerial images
Abdelmalek Bouguettaya, Hafed Zarzour, Ahmed Kechida, et al.
Cluster Computing (2022) Vol. 26, Iss. 2, pp. 1297-1317
Open Access | Times Cited: 86
UAV remote sensing detection of tea leaf blight based on DDMA-YOLO
Wenxia Bao, Z. Q. Zhu, Gensheng Hu, et al.
Computers and Electronics in Agriculture (2023) Vol. 205, pp. 107637-107637
Closed Access | Times Cited: 59
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
Hyperspectral Image Analysis and Machine Learning Techniques for Crop Disease Detection and Identification: A Review
Yimy Edisson García Vera, Mauricio Andrés Polochè Arango, Camilo A. Mendivelso-Fajardo, et al.
Sustainability (2024) Vol. 16, Iss. 14, pp. 6064-6064
Open Access | Times Cited: 20
Plant Disease Diagnosis Using Deep Learning Based on Aerial Hyperspectral Images: A Review
Lukas Wiku Kuswidiyanto, Hyun Ho Noh, Xiongzhe Han
Remote Sensing (2022) Vol. 14, Iss. 23, pp. 6031-6031
Open Access | Times Cited: 46
A systematic analysis of machine learning and deep learning based approaches for identifying and diagnosing plant diseases
Imtiaz Ahmed, Pramod Kumar Yadav
Sustainable Operations and Computers (2023) Vol. 4, pp. 96-104
Open Access | Times Cited: 35
A Review on UAV-Based Applications for Plant Disease Detection and Monitoring
Louis Kouadio, Moussa El Jarroudi, Zineb Belabess, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4273-4273
Open Access | Times Cited: 34
Early detection of rubber tree powdery mildew using UAV-based hyperspectral imagery and deep learning
Tiwei Zeng, Yong Wang, Yuqi Yang, et al.
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108909-108909
Closed Access | Times Cited: 11
The Application of Deep Learning in the Whole Potato Production Chain: A Comprehensive Review
Rui-Feng Wang, Wen‐Hao Su
Agriculture (2024) Vol. 14, Iss. 8, pp. 1225-1225
Open Access | Times Cited: 9
A Systematized Review on the Applications of Hyperspectral Imaging for Quality Control of Potatoes
Carlos Miguel Peraza-Alemán, Ainara López-Maestresalas, Carmen Jarén, et al.
Potato Research (2024) Vol. 67, Iss. 4, pp. 1539-1561
Open Access | Times Cited: 8
Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?
Alessandro Matese, Joby M. Prince Czarnecki, Sathishkumar Samiappan, et al.
Trends in Plant Science (2023) Vol. 29, Iss. 2, pp. 196-209
Open Access | Times Cited: 22
Identification of symptoms related to potato Verticillium wilt from UAV-based multispectral imagery using an ensemble of gradient boosting machines
Iván Lizarazo, J Rodriguez, Omar Cristancho, et al.
Smart Agricultural Technology (2022) Vol. 3, pp. 100138-100138
Open Access | Times Cited: 26
Airborne hyperspectral imaging for early diagnosis of kimchi cabbage downy mildew using 3D-ResNet and leaf segmentation
Lukas Wiku Kuswidiyanto, Ping‐An Wang, Hyun Ho Noh, et al.
Computers and Electronics in Agriculture (2023) Vol. 214, pp. 108312-108312
Closed Access | Times Cited: 14
Detection and Identification of Potato-Typical Diseases Based on Multidimensional Fusion Atrous-CNN and Hyperspectral Data
Wenqiang Gao, Zhiyun Xiao, Tengfei Bao
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 5023-5023
Open Access | Times Cited: 13
Potato late blight severity monitoring based on the relief-mRmR algorithm with dual-drone cooperation
Heguang Sun, Xiaoyu Song, Wei Guo, et al.
Computers and Electronics in Agriculture (2023) Vol. 215, pp. 108438-108438
Closed Access | Times Cited: 13
A survey of unmanned aerial vehicles and deep learning in precision agriculture
Dashuai Wang, Minghu Zhao, Zhuolin Li, et al.
European Journal of Agronomy (2024) Vol. 164, pp. 127477-127477
Closed Access | Times Cited: 5
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
Leveraging Convolutional Neural Networks for Disease Detection in Vegetables: A Comprehensive Review
Muhammad Mahmood ur Rehman, Jizhan Liu, Aneela Nijabat, et al.
Agronomy (2024) Vol. 14, Iss. 10, pp. 2231-2231
Open Access | Times Cited: 4
Current understanding and future perspectives on pathogen biology and management of potato and tomato late blight ( Phytophthora infestans ) in Canada
Segun Babarinde, Khalil I. Al-Mughrabi, Rishi R. Burlakoti, et al.
Canadian Journal of Plant Pathology (2025), pp. 1-21
Open Access
Large-Scale Monitoring of Potatoes Late Blight Using Multi-Source Time-Series Data and Google Earth Engine
Zelong Chi, Hong Chen, Sheng Chang, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 978-978
Open Access
Potato plant phenotyping and characterisation utilising machine learning techniques: A state-of-the-art review and current trends
Ciarán Miceal Johnson, Juan Sebastian Estrada, Fernando Auat Cheein
Computers and Electronics in Agriculture (2025) Vol. 234, pp. 110304-110304
Open Access
Modern Trends and Recent Applications of Hyperspectral Imaging: A Review
Minkang Cheng, Arvind Mukundan, Riya Karmakar, et al.
Technologies (2025) Vol. 13, Iss. 5, pp. 170-170
Open Access
Assessing the advancement of artificial intelligence and drones’ integration in agriculture through a bibliometric study
Hicham Slimani, Jamal El Mhamdi, Abdelilah Jilbab
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2023) Vol. 14, Iss. 1, pp. 878-878
Open Access | Times Cited: 9
Potato Crop Disease Prediction using Deep Learning
Karthik Kasani, Sunanda Yadla, Sadhwika Rachamalla, et al.
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) (2023), pp. 231-235
Closed Access | Times Cited: 7
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