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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:

Precise Agriculture: Effective Deep Learning Strategies to Detect Pest Insects
Luca Butera, Alberto Ferrante, Mauro Jermini, et al.
IEEE/CAA Journal of Automatica Sinica (2021) Vol. 9, Iss. 2, pp. 246-258
Closed Access | Times Cited: 47

Showing 1-25 of 47 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: 434
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: 77
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: 47
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: 20
A high performance-oriented AI-enabled IoT-based pest detection system using sound analytics in large agricultural field
Md. Akkas Ali, Rajesh Kumar Dhanaraj, Anand Nayyar
Microprocessors and Microsystems (2023) Vol. 103, pp. 104946-104946
Closed Access | Times Cited: 29
Exploring Deep Ensemble Model for Insect and Pest Detection from Images
Zeba Anwar, Sarfaraz Masood
Procedia Computer Science (2023) Vol. 218, pp. 2328-2337
Open Access | Times Cited: 26
A vision of precision agriculture: Balance between agricultural sustainability and environmental stewardship
Soumitra Nath
Agronomy Journal (2023) Vol. 116, Iss. 3, pp. 1126-1143
Closed Access | Times Cited: 25
A lightweight and enhanced model for detecting the Neotropical brown stink bug, Euschistus heros (Hemiptera: Pentatomidae) based on YOLOv8 for soybean fields
Bruno Pinheiro de Melo Lima, Lurdineide de Araújo Barbosa Borges, Edson Hirose, et al.
Ecological Informatics (2024) Vol. 80, pp. 102543-102543
Open Access | Times Cited: 15
AI-enabled IoT-based pest prevention and controlling system using sound analytics in large agricultural field
Md. Akkas Ali, Rajesh Kumar Dhanaraj, Seifedine Kadry
Computers and Electronics in Agriculture (2024) Vol. 220, pp. 108844-108844
Closed Access | Times Cited: 10
An Improved Deep Residual Convolutional Neural Network for Plant Leaf Disease Detection
J. Arun Pandian, K. Kanchanadevi, N. R. Rajalakshmi, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-9
Open Access | Times Cited: 25
Bridge detection method for HSRRSIs based on YOLOv5 with a decoupled head
Mulan Qiu, Liang Huang, Bo‐Hui Tang
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 113-129
Open Access | Times Cited: 16
Detecting common coccinellids found in sorghum using deep learning models
Chaoxin Wang, Ivan Grijalva, Doina Caragea, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
Detection of the Pine Wilt Disease Using a Joint Deep Object Detection Model Based on Drone Remote Sensing Data
Youping Wu, Honglei Yang, Yunlei Mao
Forests (2024) Vol. 15, Iss. 5, pp. 869-869
Open Access | Times Cited: 5
New trends in detection of harmful insects and pests in modern agriculture using artificial neural networks. a review
Dan Popescu, Alexandru Dinca, Loretta Ichim, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 12
Rice-YOLO: An Automated Insect Monitoring in Rice Storage Warehouses with the Deep Learning Model
P. Vinass Jamali, V. Eyarkai Nambi, M. Loganathan, et al.
ACS Agricultural Science & Technology (2025)
Closed Access
An Efficient Ground-aerial Transportation System for Pest Control Enabled by AI-based Autonomous Nano-UAVs
Luca Crupi, Luca Butera, Alberto Ferrante, et al.
ACM Journal on Autonomous Transportation Systems (2025)
Open Access
Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions
Quang Dung Dinh, Daniel Kunk, Truong Son Hy, et al.
PLoS ONE (2025) Vol. 20, Iss. 4, pp. e0319484-e0319484
Open Access
A transfer learning approach to classify insect diversity based on explainable AI
Md. Mahmudul Hasan, SM Shaqib, Sharmin Akter, et al.
Discover Life (2025) Vol. 55, Iss. 1
Open Access
Insect recognition based on complementary features from multiple views
Jingmin An, Yong Du, Peng Hong, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 10
Deep Multibranch Fusion Residual Network and IoT-based pest detection system using sound analytics in large agricultural field
Rajesh Kumar Dhanaraj, Md. Akkas Ali, Anupam Kumar Sharma, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 13, pp. 40215-40252
Closed Access | Times Cited: 9
Precision Corn Pest Detection: Two-Step Transfer Learning for Beetles (Coleoptera) with MobileNet-SSD
E. Maican, A. Iosif, Sanda Maican
Agriculture (2023) Vol. 13, Iss. 12, pp. 2287-2287
Open Access | Times Cited: 9
A Lightweight Pest Detection Model for Drones Based on Transformer and Super-Resolution Sampling Techniques
Yuzhe Bai, Fengjun Hou, Xinyuan Fan, et al.
Agriculture (2023) Vol. 13, Iss. 9, pp. 1812-1812
Open Access | Times Cited: 7
An improved deep convolutional neural network for detecting plant leaf diseases
J. Arun Pandian, K. Kanchanadevi
Concurrency and Computation Practice and Experience (2022) Vol. 34, Iss. 28
Closed Access | Times Cited: 9
Computer Vision and Deep Learning for Precise Agriculture: A Case Study of Lemon Leaf Image Classification
Yang Yuan
Journal of Physics Conference Series (2023) Vol. 2547, Iss. 1, pp. 012024-012024
Open Access | Times Cited: 5
A Scheme for Pest-Dense Area Localization With Solar Insecticidal Lamps Internet of Things Under Asymmetric Links
Yuan Li, Bangsong Du, Lin Luo, et al.
IEEE Transactions on AgriFood Electronics (2023) Vol. 1, Iss. 2, pp. 71-85
Closed Access | Times Cited: 4
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