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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:

A new mobile application of agricultural pests recognition using deep learning in cloud computing system
Mohamed Esmail Karar, Fahad Alsunaydi, Sultan Albusaymi, et al.
Alexandria Engineering Journal (2021) Vol. 60, Iss. 5, pp. 4423-4432
Open Access | Times Cited: 184

Showing 1-25 of 184 citing articles:

Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming
Tawseef Ayoub Shaikh, Tabasum Rasool, Faisal Rasheed Lone
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107119-107119
Closed Access | Times Cited: 422
Automation and digitization of agriculture using artificial intelligence and internet of things
A. Subeesh, C. R. Mehta
Artificial Intelligence in Agriculture (2021) Vol. 5, pp. 278-291
Open Access | Times Cited: 245
Classification and detection of insects from field images using deep learning for smart pest management: A systematic review
Wenyong Li, Tengfei Zheng, Zhankui Yang, et al.
Ecological Informatics (2021) Vol. 66, pp. 101460-101460
Open Access | Times Cited: 141
Deep Learning Based Detector YOLOv5 for Identifying Insect Pests
Iftikhar Ahmad, Yayun Yang, Yi Yue, et al.
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 10167-10167
Open Access | Times Cited: 103
Machine Learning for Smart Agriculture and Precision Farming: Towards Making the Fields Talk
Tawseef Ayoub Shaikh, Waseem Ahmad Mir, Tabasum Rasool, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 4557-4597
Closed Access | Times Cited: 72
MobileNet-CA-YOLO: An Improved YOLOv7 Based on the MobileNetV3 and Attention Mechanism for Rice Pests and Diseases Detection
Liangquan Jia, Tao Wang, Yi Chen, et al.
Agriculture (2023) Vol. 13, Iss. 7, pp. 1285-1285
Open Access | Times Cited: 58
Maize-YOLO: A New High-Precision and Real-Time Method for Maize Pest Detection
Shuai Yang, Ziyao Xing, Hengbin Wang, et al.
Insects (2023) Vol. 14, Iss. 3, pp. 278-278
Open Access | Times Cited: 53
Survey on crop pest detection using deep learning and machine learning approaches
M. Chithambarathanu, M. K. Jeyakumar
Multimedia Tools and Applications (2023) Vol. 82, Iss. 27, pp. 42277-42310
Open Access | Times Cited: 52
Sustainable AI-based production agriculture: Exploring AI applications and implications in agricultural practices
A.A. Mana, A. Allouhi, Abderrachid Hamrani, et al.
Smart Agricultural Technology (2024) Vol. 7, pp. 100416-100416
Open Access | Times Cited: 50
A Systematic Review on Automatic Insect Detection Using Deep Learning
Ana Cláudia Teixeira, José Ribeiro, Raul Morais, et al.
Agriculture (2023) Vol. 13, Iss. 3, pp. 713-713
Open Access | Times Cited: 44
YOLO-Based Light-Weight Deep Learning Models for Insect Detection System with Field Adaption
Nithin Kumar, Nagarathna Nagarathna, Francesco Flammini
Agriculture (2023) Vol. 13, Iss. 3, pp. 741-741
Open Access | Times Cited: 44
Evaluation of Machine Learning Approaches for Precision Farming in Smart Agriculture System: A Comprehensive Review
Ghulam Mohyuddin, Muhammad Adnan Khan, Abdul Haseeb, et al.
IEEE Access (2024) Vol. 12, pp. 60155-60184
Open Access | Times Cited: 15
Recognizing Wheat Aphid Disease Using a Novel Parallel Real-Time Technique Based on Mask Scoring RCNN
Vinay Kukreja, Deepak Kumar, Ankit Bansal, et al.
2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (2022), pp. 1372-1377
Closed Access | Times Cited: 59
Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art
Chrysanthos Maraveas
Applied Sciences (2022) Vol. 13, Iss. 1, pp. 14-14
Open Access | Times Cited: 58
COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans
Jasjit S. Suri, Sushant Agarwal, Gian Luca Chabert, et al.
Diagnostics (2022) Vol. 12, Iss. 6, pp. 1482-1482
Open Access | Times Cited: 49
Explainable deep convolutional neural networks for insect pest recognition
Solemane Coulibaly, Bernard Kamsu-Foguem, Dantouma Kamissoko, et al.
Journal of Cleaner Production (2022) Vol. 371, pp. 133638-133638
Open Access | Times Cited: 45
Deep learning based automated disease detection and pest classification in Indian mung bean
MD Tausif Mallick, Shrijeet Biswas, Amit Kumar Das, et al.
Multimedia Tools and Applications (2022) Vol. 82, Iss. 8, pp. 12017-12041
Closed Access | Times Cited: 45
Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network
Zi-xian Liu, Guansan Du, Shuai Zhou, et al.
Computational Economics (2022) Vol. 59, Iss. 4, pp. 1481-1499
Closed Access | Times Cited: 44
Insect counting through deep learning-based density maps estimation
Arantza Bereciartua, Laura Gómez-Zamanillo, Artzai Picón, et al.
Computers and Electronics in Agriculture (2022) Vol. 197, pp. 106933-106933
Closed Access | Times Cited: 44
Automatic crop disease recognition by improved abnormality segmentation along with heuristic-based concatenated deep learning model
Nafees Akhter Farooqui, Amit Kumar Mishra, Ritika Mehra
Intelligent Decision Technologies (2022) Vol. 16, Iss. 2, pp. 407-429
Closed Access | Times Cited: 43
Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering
Chrysanthos Maraveas, Panagiotis G. Asteris, Konstantinos G. Arvanitis, et al.
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 3, pp. 1979-2012
Open Access | Times Cited: 42
Recommending Advanced Deep Learning Models for Efficient Insect Pest Detection
Wei Li, Tengfei Zhu, Xiaoyu Li, et al.
Agriculture (2022) Vol. 12, Iss. 7, pp. 1065-1065
Open Access | Times Cited: 41
IoT-Enabled Pest Identification and Classification with New Meta-Heuristic-Based Deep Learning Framework
Atul B. Kathole, Kapil Vhatkar, Sonali Patil
Cybernetics & Systems (2022) Vol. 55, Iss. 2, pp. 380-408
Open Access | Times Cited: 37
A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton
Denis Olgen Kiobia, Canicius Mwitta, Kadeghe G. Fue, et al.
Sensors (2023) Vol. 23, Iss. 8, pp. 4127-4127
Open Access | Times Cited: 27
Unravelling the use of artificial intelligence in management of insect pests
B. Kariyanna, M Sowjanya
Smart Agricultural Technology (2024) Vol. 8, pp. 100517-100517
Open Access | Times Cited: 8
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