Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery
Junfeng Gao, David Nuyttens, Peter Lootens, et al.
Biosystems Engineering (2018) Vol. 170, pp. 39-50
Closed Access | Times Cited: 163

Showing 1-25 of 163 citing articles:

Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture
Bing Lu, Phuong D. Dao, Jiangui Liu, et al.
Remote Sensing (2020) Vol. 12, Iss. 16, pp. 2659-2659
Open Access | Times Cited: 740
Machine Learning in Agriculture: A Comprehensive Updated Review
Lefteris Benos, Aristotelis C. Tagarakis, Georgios Dolias, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3758-3758
Open Access | Times Cited: 526
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: 451
Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
Precision Agriculture (2021) Vol. 22, Iss. 6, pp. 2053-2091
Closed Access | Times Cited: 268
A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming
Nahina Islam, Md. Mamunur Rashid, Faezeh Pasandideh, et al.
Sustainability (2021) Vol. 13, Iss. 4, pp. 1821-1821
Open Access | Times Cited: 191
Deep convolutional neural networks for image-based Convolvulus sepium detection in sugar beet fields
Junfeng Gao, Andrew P. French, Michael P. Pound, et al.
Plant Methods (2020) Vol. 16, Iss. 1
Open Access | Times Cited: 162
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: 161
Performance of deep learning models for classifying and detecting common weeds in corn and soybean production systems
Aanis Ahmad, Dharmendra Saraswat, Varun Aggarwal, et al.
Computers and Electronics in Agriculture (2021) Vol. 184, pp. 106081-106081
Open Access | Times Cited: 136
Weed detection in soybean crops using custom lightweight deep learning models
Najmeh Razfar, Julian True, Rodina Bassiouny, et al.
Journal of Agriculture and Food Research (2022) Vol. 8, pp. 100308-100308
Open Access | Times Cited: 106
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: 78
Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review
Gustavo A. Mesías-Ruiz, María Pérez‐Ortiz, José Dorado, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 69
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: 59
Towards sustainable agriculture: Harnessing AI for global food security
Dhananjay K. Pandey, Richa Mishra
Artificial Intelligence in Agriculture (2024) Vol. 12, pp. 72-84
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: 24
A comprehensive survey on weed and crop classification using machine learning and deep learning
Faisal Dharma Adhinata, Wahyono Wahyono, Raden Sumiharto
Artificial Intelligence in Agriculture (2024) Vol. 13, pp. 45-63
Open Access | Times Cited: 18
Weed Detection for Selective Spraying: a Review
Bo Liu, Ryan Bruch
Current Robotics Reports (2020) Vol. 1, Iss. 1, pp. 19-26
Closed Access | Times Cited: 132
Advanced Machine Learning in Point Spectroscopy, RGB- and Hyperspectral-Imaging for Automatic Discriminations of Crops and Weeds: A Review
Wen‐Hao Su
Smart Cities (2020) Vol. 3, Iss. 3, pp. 767-792
Open Access | Times Cited: 97
UAS-Based Plant Phenotyping for Research and Breeding Applications
Wei Guo, Matthew E. Carroll, Arti Singh, et al.
Plant Phenomics (2021) Vol. 2021
Open Access | Times Cited: 95
Automatic late blight lesion recognition and severity quantification based on field imagery of diverse potato genotypes by deep learning
Junfeng Gao, Jesper Cairo Westergaard, Ea Høegh Riis Sundmark, et al.
Knowledge-Based Systems (2021) Vol. 214, pp. 106723-106723
Open Access | Times Cited: 78
Review of Current Robotic Approaches for Precision Weed Management
Wen Zhang, Zhonghua Miao, Nan Li, et al.
Current Robotics Reports (2022) Vol. 3, Iss. 3, pp. 139-151
Open Access | Times Cited: 68
A novel transfer deep learning method for detection and classification of plant leaf disease
Prabhjot Kaur, Shilpi Harnal, Vinay Gautam, et al.
Journal of Ambient Intelligence and Humanized Computing (2022) Vol. 14, Iss. 9, pp. 12407-12424
Closed Access | Times Cited: 65
A Review of Flying Ad Hoc Networks: Key Characteristics, Applications, and Wireless Technologies
Faezeh Pasandideh, João Paulo C. L. da Costa, Rafael Kunst, et al.
Remote Sensing (2022) Vol. 14, Iss. 18, pp. 4459-4459
Open Access | Times Cited: 44
Metaheuristic Optimization for Improving Weed Detection in Wheat Images Captured by Drones
El-Sayed M. El-kenawy, Nima Khodadadi, Seyedali Mirjalili, et al.
Mathematics (2022) Vol. 10, Iss. 23, pp. 4421-4421
Open Access | Times Cited: 44
Classification of paddy crop and weeds using semantic segmentation
Radhika Kamath, Mamatha Balachandra, Amodini Vardhan, et al.
Cogent Engineering (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 41
SE-YOLOv5x: An Optimized Model Based on Transfer Learning and Visual Attention Mechanism for Identifying and Localizing Weeds and Vegetables
Jianlin Zhang, Wen‐Hao Su, Heyi Zhang, et al.
Agronomy (2022) Vol. 12, Iss. 9, pp. 2061-2061
Open Access | Times Cited: 40
Page 1 - Next Page

Scroll to top