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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:

An integrated rice panicle phenotyping method based on X-ray and RGB scanning and deep learning
Lejun Yu, Jiawei Shi, Chenglong Huang, et al.
The Crop Journal (2020) Vol. 9, Iss. 1, pp. 42-56
Open Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics
Jacob I. Marsh, Haifei Hu, Mitchell Gill, et al.
Theoretical and Applied Genetics (2021) Vol. 134, Iss. 6, pp. 1677-1690
Closed Access | Times Cited: 59
Quick and accurate monitoring peanut seedlings emergence rate through UAV video and deep learning
Yongda Lin, Tingting Chen, Shiyuan Liu, et al.
Computers and Electronics in Agriculture (2022) Vol. 197, pp. 106938-106938
Closed Access | Times Cited: 50
AIseed: An automated image analysis software for high-throughput phenotyping and quality non-destructive testing of individual plant seeds
Keling Tu, Weifeng Wu, Ying Cheng, et al.
Computers and Electronics in Agriculture (2023) Vol. 207, pp. 107740-107740
Closed Access | Times Cited: 21
A model for genuineness detection in genetically and phenotypically similar maize variety seeds based on hyperspectral imaging and machine learning
Keling Tu, Shaozhe Wen, Ying Cheng, et al.
Plant Methods (2022) Vol. 18, Iss. 1
Open Access | Times Cited: 29
Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature
Jian Wang, Bizhi Wu, Markus V. Kohnen, et al.
Plant Phenomics (2021) Vol. 2021
Open Access | Times Cited: 30
Ir-UNet: Irregular Segmentation U-Shape Network for Wheat Yellow Rust Detection by UAV Multispectral Imagery
Tianxiang Zhang, Zhiyong Xu, Jinya Su, et al.
Remote Sensing (2021) Vol. 13, Iss. 19, pp. 3892-3892
Open Access | Times Cited: 30
Automatic Detection and Counting of Wheat Spikelet Using Semi-Automatic Labeling and Deep Learning
Ruicheng Qiu, Yong He, Man Zhang
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 16
High-throughput and separating-free phenotyping method for on-panicle rice grains based on deep learning
Yuwei Lu, Jinhu Wang, Ling Fu, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 9
Deep Convolutional Neural Network for Rice Density Prescription Map at Ripening Stage Using Unmanned Aerial Vehicle-Based Remotely Sensed Images
Lele Wei, Yusen Luo, Lizhang Xu, et al.
Remote Sensing (2021) Vol. 14, Iss. 1, pp. 46-46
Open Access | Times Cited: 22
Challenges and opportunities in applying AI to evolutionary morphology
Yichen He, James M. Mulqueeney, Emily Watt, et al.
(2024)
Open Access | Times Cited: 2
A High-Throughput Method for Accurate Extraction of Intact Rice Panicle Traits
Jian Sun, Zhengwei Ren, Jiale Cui, et al.
Plant Phenomics (2024) Vol. 6
Open Access | Times Cited: 2
Research on Asphalt Pavement Disease Detection Based on Improved YOLOv5s
Lingxiao Wu, Zhugeng Duan, Chenghao Liang
Journal of Sensors (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 7
Automatic Identification of Sea Rice Grains in Complex Field Environment Based on Deep Learning
Ruoling Deng, Weilin Cheng, Haitao Liu, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1135-1135
Open Access | Times Cited: 1
Size measurement and filled/unfilled detection of rice grains using backlight image processing
Xiao Feng, Zhiqi Wang, Zhiwei Zeng, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 4
Deep Predictive Models Based on IoT and Remote Sensing Big Time Series for Precision Agriculture
Yahjeb Bouha Khatraty, Nédra Mellouli Nauwynck, Mamadou Tourad Diallo, et al.
International Journal of Emerging Technology and Advanced Engineering (2022) Vol. 12, Iss. 11, pp. 79-88
Open Access | Times Cited: 6
Machine learning for major food crops breeding: Applications, challenges, and ways forward
Kumanan N. Govaichelvan, Dharini Pathmanathan, Rabiatul‐Adawiah Zainal‐Abidin, et al.
Agronomy Journal (2023) Vol. 116, Iss. 3, pp. 1112-1125
Closed Access | Times Cited: 3
Seedscreener: A novel integrated wheat germplasm phenotyping platform based on NIR-feature detection and 3D-reconstruction
Tingting Wu, Jianlong Dai, Peng Shen, et al.
Computers and Electronics in Agriculture (2023) Vol. 215, pp. 108378-108378
Closed Access | Times Cited: 2
An Intelligent Rice Yield Trait Evaluation System Based on Threshed Panicle Compensation
Chenglong Huang, Weikun Li, Zhang Zhong-fu, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 4
Non-Destructive Viability Discrimination for Individual Scutellaria baicalensis Seeds Based on High-Throughput Phenotyping and Machine Learning
Keling Tu, Ying Cheng, Cuiling Ning, et al.
Agriculture (2022) Vol. 12, Iss. 10, pp. 1616-1616
Open Access | Times Cited: 4
Elevated CO2 and positional variation in cereal grains
Guoyou Zhang
Crop Science (2021) Vol. 61, Iss. 6, pp. 3859-3860
Closed Access | Times Cited: 5
Detection and Dynamic Variation Characteristics of Rice Nitrogen Status after Anthesis Based on the RGB Color Index
Kaocheng Zhao, Ying Ye, Ma Jun, et al.
Agronomy (2021) Vol. 11, Iss. 9, pp. 1739-1739
Open Access | Times Cited: 5
An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management
Wanneng Yang, Hui Feng, Xiao Hu, et al.
Methods in molecular biology (2024), pp. 3-38
Closed Access
Accurate rice grain counting in natural morphology: A method based on image classification and object detection
Jian Sun, Haoyang Jia, Zhengwei Ren, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109490-109490
Closed Access
PanicleNeRF: low-cost, high-precision in-field phenotyping of rice panicles with smartphone
Xin Yang, Xuqi Lu, Pengyao Xie, et al.
Plant Phenomics (2024) Vol. 6
Closed Access
Rice spikelet’s disease detection using hybrid optimization model and optimized CNN
Bharati Patel
Soft Computing (2024)
Closed Access
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