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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:

A near real-time deep learning approach for detecting rice phenology based on UAV images
Qi Yang, Liangsheng Shi, Jingye Han, et al.
Agricultural and Forest Meteorology (2020) Vol. 287, pp. 107938-107938
Closed Access | Times Cited: 126

Showing 1-25 of 126 citing articles:

High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms
Xiuliang Jin, Pablo J. Zarco‐Tejada, Urs Schmidhalter, et al.
IEEE Geoscience and Remote Sensing Magazine (2020) Vol. 9, Iss. 1, pp. 200-231
Open Access | Times Cited: 222
Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning, and Rice Production Tasks
Rayner Alfred, Joe Henry Obit, Christie Pei-Yee Chin, et al.
IEEE Access (2021) Vol. 9, pp. 50358-50380
Open Access | Times Cited: 134
Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review
Aya Ferchichi, Ali Ben Abbes, Vincent Barra, et al.
Ecological Informatics (2022) Vol. 68, pp. 101552-101552
Closed Access | Times Cited: 90
Artificial intelligence-based techniques for adulteration and defect detections in food and agricultural industry: A review
Suhaili Othman, Nidhi Rajesh Mavani, M.A. Hussain, et al.
Journal of Agriculture and Food Research (2023) Vol. 12, pp. 100590-100590
Open Access | Times Cited: 45
Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities
Zheng Gong, Wenyan Ge, Jiaqi Guo, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 217, pp. 149-164
Closed Access | Times Cited: 28
Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
Salvador Castillo‐Gironés, Sandra Munera, Marcelino Martínez‐Sober, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109938-109938
Open Access | Times Cited: 4
Soil organic carbon prediction using phenological parameters and remote sensing variables generated from Sentinel-2 images
Xianglin He, Lin Yang, Anqi Li, et al.
CATENA (2021) Vol. 205, pp. 105442-105442
Closed Access | Times Cited: 87
Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest
Kasper Johansen, Mitchell J. L. Morton, Yoann Malbéteau, et al.
Frontiers in Artificial Intelligence (2020) Vol. 3
Open Access | Times Cited: 85
An Architectural Multi-Agent System for a Pavement Monitoring System with Pothole Recognition in UAV Images
Luís Augusto Silva, Héctor Sánchez San Blas, David Peral García, et al.
Sensors (2020) Vol. 20, Iss. 21, pp. 6205-6205
Open Access | Times Cited: 77
Remote estimation of grain yield based on UAV data in different rice cultivars under contrasting climatic zone
Bo Duan, Shenghui Fang, Yan Gong, et al.
Field Crops Research (2021) Vol. 267, pp. 108148-108148
Closed Access | Times Cited: 72
An intelligent system for crop identification and classification from UAV images using conjugated dense convolutional neural network
Akshay Pandey, Kamal Jain
Computers and Electronics in Agriculture (2021) Vol. 192, pp. 106543-106543
Closed Access | Times Cited: 66
Deep Learning in Plant Phenological Research: A Systematic Literature Review
Negin Katal, Michael Rzanny, Patrick Mäder, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 50
Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model
Shaoyu Han, Yu Zhao, Jinpeng Cheng, et al.
Remote Sensing (2022) Vol. 14, Iss. 15, pp. 3723-3723
Open Access | Times Cited: 41
Developing an operational algorithm for near-real-time monitoring of crop progress at field scales by fusing harmonized Landsat and Sentinel-2 time series with geostationary satellite observations
Yu Shen, Xiaoyang Zhang, Zhengwei Yang, et al.
Remote Sensing of Environment (2023) Vol. 296, pp. 113729-113729
Open Access | Times Cited: 28
PhenoNet: A two-stage lightweight deep learning framework for real-time wheat phenophase classification
Ruinan Zhang, Shichao Jin, Yuanhao Zhang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 208, pp. 136-157
Closed Access | Times Cited: 12
Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques
Chinna Gopi Simhadri, Hari Kishan Kondaveeti, V. Valli Kumari, et al.
Information Processing in Agriculture (2024)
Open Access | Times Cited: 12
Real-time monitoring of maize phenology with the VI-RGS composite index using time-series UAV remote sensing images and meteorological data
Ziheng Feng, Zhida Cheng, Lipeng Ren, et al.
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109212-109212
Closed Access | Times Cited: 9
Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking
Ziheng Feng, Jiliang Zhao, Liunan Suo, et al.
The Crop Journal (2025)
Open Access | Times Cited: 1
Maize tasseling date forecast from canopy height time series estimated by UAV LiDAR data
Yadong Liu, Chenwei Nie, Liang Li, et al.
The Crop Journal (2025)
Open Access | Times Cited: 1
An Internet of Things assisted Unmanned Aerial Vehicle based artificial intelligence model for rice pest detection
Sourav Kumar Bhoi, Kalyan Kumar Jena, Sanjaya Kumar Panda, et al.
Microprocessors and Microsystems (2020) Vol. 80, pp. 103607-103607
Closed Access | Times Cited: 65
Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images
Mohamed Barakat A. Gibril, Helmi Zulhaidi Mohd Shafri, Abdallah Shanableh, et al.
Remote Sensing (2021) Vol. 13, Iss. 14, pp. 2787-2787
Open Access | Times Cited: 42
Mapping corn and soybean phenometrics at field scales over the United States Corn Belt by fusing time series of Landsat 8 and Sentinel-2 data with VIIRS data
Yu Shen, Xiaoyang Zhang, Zhengwei Yang
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 186, pp. 55-69
Open Access | Times Cited: 37
Advanced Technology in Agriculture Industry by Implementing Image Annotation Technique and Deep Learning Approach: A Review
Normaisharah Mamat, Mohd Fauzi Othman, Rawad Abdoulghafor, et al.
Agriculture (2022) Vol. 12, Iss. 7, pp. 1033-1033
Open Access | Times Cited: 34
UAV time-series imagery with novel machine learning to estimate heading dates of rice accessions for breeding
Mengqi Lyu, Xuqi Lu, Yutao Shen, et al.
Agricultural and Forest Meteorology (2023) Vol. 341, pp. 109646-109646
Closed Access | Times Cited: 23
Application of Deep Learning in Multitemporal Remote Sensing Image Classification
Xinglu Cheng, Yonghua Sun, Wangkuan Zhang, et al.
Remote Sensing (2023) Vol. 15, Iss. 15, pp. 3859-3859
Open Access | Times Cited: 22
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