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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:

Computer vision technology in agricultural automation —A review
Hongkun Tian, Tianhai Wang, Yadong Liu, et al.
Information Processing in Agriculture (2019) Vol. 7, Iss. 1, pp. 1-19
Open Access | Times Cited: 507

Showing 1-25 of 507 citing articles:

Machine Learning Applications for Precision Agriculture: A Comprehensive Review
Abhinav Sharma, Arpit Jain, Prateek Gupta, et al.
IEEE Access (2020) Vol. 9, pp. 4843-4873
Open Access | Times Cited: 649
Review of Weed Detection Methods Based on Computer Vision
Zhangnan Wu, Yajun Chen, Bo Zhao, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3647-3647
Open Access | Times Cited: 206
Visual Perception Enabled Industry Intelligence: State of the Art, Challenges and Prospects
Jiachen Yang, Chenguang Wang, Bin Jiang, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 3, pp. 2204-2219
Open Access | Times Cited: 203
Precision Agriculture for Crop and Livestock Farming—Brief Review
António Monteiro, Sérgio Ribeiro dos Santos, Pedro Gonçalves
Animals (2021) Vol. 11, Iss. 8, pp. 2345-2345
Open Access | Times Cited: 194
Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm
Nahina Islam, Md. Mamunur Rashid, Santoso Wibowo, et al.
Agriculture (2021) Vol. 11, Iss. 5, pp. 387-387
Open Access | Times Cited: 159
Deep learning based computer vision approaches for smart agricultural applications
V. G. Dhanya, A. Subeesh, Nand Lal Kushwaha, et al.
Artificial Intelligence in Agriculture (2022) Vol. 6, pp. 211-229
Open Access | Times Cited: 159
Using deep belief network to construct the agricultural information system based on Internet of Things
Ji Luo, Chuhao Zhao, Chen Qiao, et al.
The Journal of Supercomputing (2021) Vol. 78, Iss. 1, pp. 379-405
Closed Access | Times Cited: 154
Applications of machine vision in agricultural robot navigation: A review
Tianhai Wang, Bao‐Ji Chen, Zhenqian Zhang, et al.
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107085-107085
Closed Access | Times Cited: 134
AgriSegNet: Deep Aerial Semantic Segmentation Framework for IoT-Assisted Precision Agriculture
Tanmay Anand, Soumendu Sinha, Murari Mandal, et al.
IEEE Sensors Journal (2021) Vol. 21, Iss. 16, pp. 17581-17590
Closed Access | Times Cited: 109
A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future
Susantha Wanniarachchi, Ranjan Sarukkalige
Hydrology (2022) Vol. 9, Iss. 7, pp. 123-123
Open Access | Times Cited: 92
FieldPlant: A Dataset of Field Plant Images for Plant Disease Detection and Classification With Deep Learning
Emmanuel Moupojou, Appolinaire Tagne, Florent Retraint, et al.
IEEE Access (2023) Vol. 11, pp. 35398-35410
Open Access | Times Cited: 74
Recent advancements in multimodal human–robot interaction
Hang Su, Wen Qi, Jiahao Chen, et al.
Frontiers in Neurorobotics (2023) Vol. 17
Open Access | Times Cited: 52
Mission AI
Haroon I. Sheikh, J.E.J. Prins, Erik Schrijvers
Research for policy (2023)
Open Access | Times Cited: 47
An Effective Image-Based Tomato Leaf Disease Segmentation Method Using MC-UNet
Yubao Deng, Haoran Xi, Guoxiong Zhou, et al.
Plant Phenomics (2023) Vol. 5
Open Access | Times Cited: 45
Row Detection BASED Navigation and Guidance for Agricultural Robots and Autonomous Vehicles in Row-Crop Fields: Methods and Applications
Jiayou Shi, Yuhao Bai, Zhihua Diao, et al.
Agronomy (2023) Vol. 13, Iss. 7, pp. 1780-1780
Open Access | Times Cited: 44
Computer vision in smart agriculture and precision farming: Techniques and applications
Sumaira Ghazal, Arslan Munir, Waqar S. Qureshi
Artificial Intelligence in Agriculture (2024) Vol. 13, pp. 64-83
Open Access | Times Cited: 32
Automatic fruit picking technology: a comprehensive review of research advances
Jun Zhang, Ningbo Kang, Qianjin Qu, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
Open Access | Times Cited: 25
Wheat Seed Detection and Counting Method Based on Improved YOLOv8 Model
Na Ma, Yaxin Su, Lexin Yang, et al.
Sensors (2024) Vol. 24, Iss. 5, pp. 1654-1654
Open Access | Times Cited: 24
Automation’s Impact on Agriculture: Opportunities, Challenges, and Economic Effects
Khadijeh Bazargani, Taher Deemyad
Robotics (2024) Vol. 13, Iss. 2, pp. 33-33
Open Access | Times Cited: 23
Computer vision and deep learning-based approaches for detection of food nutrients/nutrition: New insights and advances
Sushant Kaushal, Dushyanth Kumar Tammineni, Priya Rana, et al.
Trends in Food Science & Technology (2024) Vol. 146, pp. 104408-104408
Closed Access | Times Cited: 22
A Comprehensive Review on Deep Learning Assisted Computer Vision Techniques for Smart Greenhouse Agriculture
Jalal Uddin Md Akbar, Syafiq Fauzi Kamarulzaman, Abu Jafar Md Muzahid, et al.
IEEE Access (2024) Vol. 12, pp. 4485-4522
Open Access | Times Cited: 18
A comprehensive review of deep learning-based hyperspectral image reconstruction for agri-food quality appraisal
Md. Toukir Ahmed, Ocean Monjur, Alin Khaliduzzaman, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access | Times Cited: 5
Industry 4.0 Disruption and Its Neologisms in Major Industrial Sectors: A State of the Art
Ocident Bongomin, Aregawi Yemane, Brendah Kembabazi, et al.
Journal of Engineering (2020) Vol. 2020, pp. 1-45
Open Access | Times Cited: 118
Robotic Aubergine Harvesting Using Dual-Arm Manipulation
Delia Sepúlveda, Roemí Fernández, Eduardo Navas, et al.
IEEE Access (2020) Vol. 8, pp. 121889-121904
Open Access | Times Cited: 106
Exploring the relationship between ICT, SCM practices and organizational performance in agri-food supply chain
Anil Kumar, Rohit Kumar Singh, Sachin Modgil
Benchmarking An International Journal (2020) Vol. 27, Iss. 3, pp. 1003-1041
Closed Access | Times Cited: 98
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