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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:

Machine Vision Systems in Precision Agriculture for Crop Farming
Efthimia Mavridou, Εleni Vrochidou, George A. Papakostas, et al.
Journal of Imaging (2019) Vol. 5, Iss. 12, pp. 89-89
Open Access | Times Cited: 226

Showing 1-25 of 226 citing articles:

A survey of public datasets for computer vision tasks in precision agriculture
Yuzhen Lu, Sierra Young
Computers and Electronics in Agriculture (2020) Vol. 178, pp. 105760-105760
Open Access | Times Cited: 261
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: 202
Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review
Yuzhen Lu, Dong Chen, Ebenezer O. Olaniyi, et al.
Computers and Electronics in Agriculture (2022) Vol. 200, pp. 107208-107208
Open Access | Times Cited: 171
Vision-based navigation and guidance for agricultural autonomous vehicles and robots: A review
Yuhao Bai, Baohua Zhang, Naimin Xu, et al.
Computers and Electronics in Agriculture (2022) Vol. 205, pp. 107584-107584
Closed Access | Times Cited: 141
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: 91
Off-Road Electric Vehicles and Autonomous Robots in Agricultural Sector: Trends, Challenges, and Opportunities
Amin Ghobadpour, German Monsalve, Alben Cardenas, et al.
Vehicles (2022) Vol. 4, Iss. 3, pp. 843-864
Open Access | Times Cited: 79
Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review
Hasyiya Karimah Adli, Muhammad Akmal Remli, Khairul Nizar Syazwan Wan Salihin Wong, et al.
Sensors (2023) Vol. 23, Iss. 7, pp. 3752-3752
Open Access | Times Cited: 65
Smart Sensors and Smart Data for Precision Agriculture: A Review
Abdellatif Soussi, Enrico Zero, Roberto Sacile, et al.
Sensors (2024) Vol. 24, Iss. 8, pp. 2647-2647
Open Access | Times Cited: 57
Using an improved lightweight YOLOv8 model for real-time detection of multi-stage apple fruit in complex orchard environments
Baoling Ma, Zhixin Hua, Yuchen Wen, et al.
Artificial Intelligence in Agriculture (2024) Vol. 11, pp. 70-82
Open Access | Times Cited: 40
Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation
Mrutyunjay Padhiary, Debapam Saha, Raushan Kumar, et al.
Smart Agricultural Technology (2024) Vol. 8, pp. 100483-100483
Open Access | Times Cited: 33
Human-Centered AI in smart farming: Towards Agriculture 5.0
Andreas Holzinger, Iztok Fister, Iztok Fister, et al.
IEEE Access (2024) Vol. 12, pp. 62199-62214
Open Access | Times Cited: 25
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: 23
Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture
Kushagra Sharma, Shiv Kumar Shivandu
Sensors International (2024) Vol. 5, pp. 100292-100292
Open Access | Times Cited: 19
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
Vision systems for harvesting robots: Produce detection and localization
Luis-Enrique Montoya-Cavero, Rocío Díaz de León Torres, Alfonso Gómez-Espinosa, et al.
Computers and Electronics in Agriculture (2021) Vol. 192, pp. 106562-106562
Closed Access | Times Cited: 67
Benchmark of Deep Learning and a Proposed HSV Colour Space Models for the Detection and Classification of Greenhouse Tomato
Germano Moreira, Sandro Augusto Magalhães, Tatiana M. Pinho, et al.
Agronomy (2022) Vol. 12, Iss. 2, pp. 356-356
Open Access | Times Cited: 65
Plant leaf disease classification and damage detection system using deep learning models
B. Sai Reddy, S. Neeraja
Multimedia Tools and Applications (2022) Vol. 81, Iss. 17, pp. 24021-24040
Closed Access | Times Cited: 52
Technological Trends and Engineering Issues on Vertical Farms: A Review
Md Shaha Nur Kabir, Md Nasim Reza, Milon Chowdhury, et al.
Horticulturae (2023) Vol. 9, Iss. 11, pp. 1229-1229
Open Access | Times Cited: 40
A comparison between Pixel-based deep learning and Object-based image analysis (OBIA) for individual detection of cabbage plants based on UAV Visible-light images
Zhangxi Ye, Kaile Yang, Yuwei Lin, et al.
Computers and Electronics in Agriculture (2023) Vol. 209, pp. 107822-107822
Open Access | Times Cited: 39
Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture
Jaemyung Shin, Md Sultan Mahmud, Tanzeel U. Rehman, et al.
AgriEngineering (2022) Vol. 5, Iss. 1, pp. 20-39
Open Access | Times Cited: 37
Cooperative Heterogeneous Robots for Autonomous Insects Trap Monitoring System in a Precision Agriculture Scenario
Guido S. Berger, Marco Antônio Simões Teixeira, Álvaro Rogério Cantieri, et al.
Agriculture (2023) Vol. 13, Iss. 2, pp. 239-239
Open Access | Times Cited: 36
Deep-learning-based counting methods, datasets, and applications in agriculture: a review
Guy Farjon, Liu Hui-jun, Yael Edan
Precision Agriculture (2023) Vol. 24, Iss. 5, pp. 1683-1711
Closed Access | Times Cited: 35
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: 31
Deep Learning YOLO-Based Solution for Grape Bunch Detection and Assessment of Biophysical Lesions
Isabel Pinheiro, Germano Moreira, Daniel Queirós da Silva, et al.
Agronomy (2023) Vol. 13, Iss. 4, pp. 1120-1120
Open Access | Times Cited: 27
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