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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:

Deep Learning Applied to Phenotyping of Biomass in Forages with UAV-Based RGB Imagery
Wellington V. M. de Castro, José Marcato, Caio Polidoro, et al.
Sensors (2020) Vol. 20, Iss. 17, pp. 4802-4802
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Review on Convolutional Neural Networks (CNN) in vegetation remote sensing
Teja Kattenborn, Jens Leitloff, Felix Schiefer, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 173, pp. 24-49
Open Access | Times Cited: 1151
A review on deep learning in UAV remote sensing
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102456-102456
Open Access | Times Cited: 335
Precision and Digital Agriculture: Adoption of Technologies and Perception of Brazilian Farmers
Édson Luís Bolfe, Lúcio André de Castro Jorge, Ieda Del’Arco Sanches, et al.
Agriculture (2020) Vol. 10, Iss. 12, pp. 653-653
Open Access | Times Cited: 168
A Review of Estimation Methods for Aboveground Biomass in Grasslands Using UAV
Clara Oliva Gonçalves Bazzo, Bahareh Kamali, Christoph Hütt, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 639-639
Open Access | Times Cited: 45
Object detection and tracking in Precision Farming: a systematic review
Mar Ariza-Sentís, Sergio Vélez, Raquel Martínez‐Peña, et al.
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108757-108757
Open Access | Times Cited: 42
Economic and environmental benefits of digital agricultural technologies in crop production: A review
George Papadopoulos, Simone Arduini, Havva Uyar, et al.
Smart Agricultural Technology (2024) Vol. 8, pp. 100441-100441
Open Access | Times Cited: 34
Drone‐based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive review
Boubacar Gano, Sourav Bhadra, Justin M. Vilbig, et al.
The Plant Phenome Journal (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 18
Monitoring Yield and Quality of Forages and Grassland in the View of Precision Agriculture Applications—A Review
Abid Ali, Hans‐Peter Kaul
Remote Sensing (2025) Vol. 17, Iss. 2, pp. 279-279
Open Access | Times Cited: 2
Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives
Haiyu Tao, Shan Xu, Yongchao Tian, et al.
Plant Communications (2022) Vol. 3, Iss. 6, pp. 100344-100344
Open Access | Times Cited: 62
Integrating the Textural and Spectral Information of UAV Hyperspectral Images for the Improved Estimation of Rice Aboveground Biomass
Tianyue Xu, Fumin Wang, Lili Xie, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2534-2534
Open Access | Times Cited: 49
Hyperspectral-to-image transform and CNN transfer learning enhancing soybean LCC estimation
Jibo Yue, Hao Yang, Haikuan Feng, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108011-108011
Closed Access | Times Cited: 34
Predicting Days to Maturity, Plant Height, and Grain Yield in Soybean: A Machine and Deep Learning Approach Using Multispectral Data
Paulo Eduardo Teodoro, Larissa Pereira Ribeiro Teodoro, Fábio Henrique Rojo Baio, et al.
Remote Sensing (2021) Vol. 13, Iss. 22, pp. 4632-4632
Open Access | Times Cited: 56
ATSS Deep Learning-Based Approach to Detect Apple Fruits
Leonardo Josoé Biffi, Edson Aparecido Mitishita, Veraldo Liesenberg, et al.
Remote Sensing (2020) Vol. 13, Iss. 1, pp. 54-54
Open Access | Times Cited: 53
Multiscale Object Detection from Drone Imagery Using Ensemble Transfer Learning
Rahee Walambe, Aboli Marathe, Ketan Kotecha
Drones (2021) Vol. 5, Iss. 3, pp. 66-66
Open Access | Times Cited: 47
A Convolutional Neural Network-Based Method for Corn Stand Counting in the Field
Le Wang, Lirong Xiang, Lie Tang, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 507-507
Open Access | Times Cited: 44
Estimation of Aboveground Carbon Density of Forests Using Deep Learning and Multisource Remote Sensing
Fanyi Zhang, Xin Tian, Haibo Zhang, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 3022-3022
Open Access | Times Cited: 34
Deep Learning for Strawberry Canopy Delineation and Biomass Prediction from High-Resolution Images
Caiwang Zheng, Amr Abd‐Elrahman, Vance M. Whitaker, et al.
Plant Phenomics (2022) Vol. 2022
Open Access | Times Cited: 34
Deep Learning Enables Instant and Versatile Estimation of Rice Yield Using Ground-Based RGB Images
Yu Tanaka, Tomoya Watanabe, Keisuke Katsura, et al.
Plant Phenomics (2023) Vol. 5
Open Access | Times Cited: 17
Improving Accuracy of Herbage Yield Predictions in Perennial Ryegrass with UAV-Based Structural and Spectral Data Fusion and Machine Learning
Joanna Pranga, Irene Borra‐Serrano, Jonas Aper, et al.
Remote Sensing (2021) Vol. 13, Iss. 17, pp. 3459-3459
Open Access | Times Cited: 35
Phenotypic Traits Estimation and Preliminary Yield Assessment in Different Phenophases of Wheat Breeding Experiment Based on UAV Multispectral Images
Dessislava Ganeva, Eugenia Roumenina, Petar Dimitrov, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 1019-1019
Open Access | Times Cited: 27
Using Unmanned Aerial Vehicles and Multispectral Sensors to Model Forage Yield for Grasses of Semiarid Landscapes
Alexander J. Hernández, Kevin B. Jensen, Steve Larson, et al.
Grasses (2024) Vol. 3, Iss. 2, pp. 84-109
Open Access | Times Cited: 5
The Development and Application of Machine Learning in Atmospheric Environment Studies
Lianming Zheng, Rui Lin, Xuemei Wang, et al.
Remote Sensing (2021) Vol. 13, Iss. 23, pp. 4839-4839
Open Access | Times Cited: 31
Genomic Selection in Tropical Forage Grasses: Current Status and Future Applications
R. M. S. Resende, Marcos Deon Vilela de Resende, Rodrigo Silva Alves, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 30
Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks
Kirsi Karila, Raquel Alves de Oliveira, Johannes Ek, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2692-2692
Open Access | Times Cited: 20
An Overview of Using Unmanned Aerial System Mounted Sensors to Measure Plant Above-Ground Biomass
Aliasghar Bazrafkan, Nadia Delavarpour, Peter G. Oduor, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3543-3543
Open Access | Times Cited: 11
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