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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:

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

Showing 1-25 of 159 citing articles:

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: 516
A Systematic Literature Review on Crop Yield Prediction with Deep Learning and Remote Sensing
Priyanga Muruganantham, Santoso Wibowo, Srimannarayana Grandhi, et al.
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 1990-1990
Open Access | Times Cited: 175
A Comprehensive Survey of the Recent Studies with UAV for Precision Agriculture in Open Fields and Greenhouses
Muhammet Fatih Aslan, Akif Durdu, Kadir Sabancı, et al.
Applied Sciences (2022) Vol. 12, Iss. 3, pp. 1047-1047
Open Access | Times Cited: 168
Remote Sensing in Field Crop Monitoring: A Comprehensive Review of Sensor Systems, Data Analyses and Recent Advances
Emmanuel Omia, Hyungjin Bae, Eunsung Park, et al.
Remote Sensing (2023) Vol. 15, Iss. 2, pp. 354-354
Open Access | Times Cited: 120
Applications of deep learning in precision weed management: A review
Nitin Rai, Yu Zhang, Billy G. Ram, et al.
Computers and Electronics in Agriculture (2023) Vol. 206, pp. 107698-107698
Open Access | Times Cited: 111
UAV-based weed detection in Chinese cabbage using deep learning
Pauline Ong, Kiat Soon Teo, Sia Chee Kiong
Smart Agricultural Technology (2023) Vol. 4, pp. 100181-100181
Open Access | Times Cited: 48
Machine learning in agriculture: a review of crop management applications
Ishana Attri, Lalit Kumar Awasthi, Teek Parval Sharma
Multimedia Tools and Applications (2023) Vol. 83, Iss. 5, pp. 12875-12915
Closed Access | Times Cited: 47
Revolutionizing Agriculture: A Comprehensive Review of Artificial Intelligence Techniques in Farming
Gautam Siddharth Kashyap, Prerna Kamani, Malvika Kanojia, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 38
Deep Learning-Based Weed–Crop Recognition for Smart Agricultural Equipment: A Review
Hao-Ran Qu, Wen‐Hao Su
Agronomy (2024) Vol. 14, Iss. 2, pp. 363-363
Open Access | Times Cited: 20
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
Urban Tree Classification Based on Object-Oriented Approach and Random Forest Algorithm Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery
Qian Guo, Jian Zhang, Shijie Guo, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3885-3885
Open Access | Times Cited: 66
Performance evaluation of deep learning object detectors for weed detection for cotton
Abdur Rahman, Yuzhen Lu, Haifeng Wang
Smart Agricultural Technology (2022) Vol. 3, pp. 100126-100126
Open Access | Times Cited: 60
Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A Review
Ildar Rakhmatulin, Andreas Kamilaris, Christian Andreasen
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4486-4486
Open Access | Times Cited: 57
Computer Vision and Deep Learning-enabled Weed Detection Model for Precision Agriculture
R. Punithavathi, A. Delphin Carolina Rani, K. R. Sughashini, et al.
Computer Systems Science and Engineering (2022) Vol. 44, Iss. 3, pp. 2759-2774
Open Access | Times Cited: 46
Deep learning-based early weed segmentation using motion blurred UAV images of sorghum fields
Nikita Genze, Raymond Ajekwe, Zeynep Güreli, et al.
Computers and Electronics in Agriculture (2022) Vol. 202, pp. 107388-107388
Open Access | Times Cited: 45
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: 41
A comprehensive survey on IoT and AI based applications in different pre-harvest, during-harvest and post-harvest activities of smart agriculture
Rohit Kumar Kasera, Shivashish Gour, Tapodhir Acharjee
Computers and Electronics in Agriculture (2023) Vol. 216, pp. 108522-108522
Closed Access | Times Cited: 38
Segmentation of weeds and crops using multispectral imaging and CRF-enhanced U-Net
Halil Mertkan Sahin, Tajul Miftahushudur, Bruce Grieve, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 107956-107956
Open Access | Times Cited: 32
Instance segmentation method for weed detection using UAV imagery in soybean fields
Beibei Xu, Jiahao Fan, Jun Chao, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 107994-107994
Open Access | Times Cited: 32
Artificial Intelligence Tools and Techniques to Combat Herbicide Resistant Weeds—A Review
Shirin Ghatrehsamani, Gaurav Jha, Writuparna Dutta, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 1843-1843
Open Access | Times Cited: 31
Weed Identification in Soybean Seedling Stage Based on Optimized Faster R-CNN Algorithm
Xinle Zhang, Jian Cui, Huanjun Liu, et al.
Agriculture (2023) Vol. 13, Iss. 1, pp. 175-175
Open Access | Times Cited: 27
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: 15
Advanced drone-based weed detection using feature-enriched deep learning approach
Mobeen Ur Rehman, Hassan Eesaar, Zeeshan Abbas, et al.
Knowledge-Based Systems (2024), pp. 112655-112655
Open Access | Times Cited: 12
Development of an early detection and automatic targeting system for cotton weeds using an improved lightweight YOLOv8 architecture on an edge device
Md. Jawadul Karim, Md. Nahiduzzaman, Mominul Ahsan, et al.
Knowledge-Based Systems (2024) Vol. 300, pp. 112204-112204
Open Access | Times Cited: 9
Crop Detection and Maturity Classification Using a YOLOv5-Based Image Analysis
Viviana Moya, Angélica Quito, Andrea Pilco, et al.
Emerging Science Journal (2024) Vol. 8, Iss. 2, pp. 496-512
Open Access | Times Cited: 8
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