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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:

Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels
Pengliang Wei, Ran Huang, Tao Lin, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 328-328
Open Access | Times Cited: 16

Showing 16 citing articles:

Crop type mapping in the central part of the North China Plain using Sentinel-2 time series and machine learning
Ke Luo, Linlin Lu, Yanhua Xie, et al.
Computers and Electronics in Agriculture (2022) Vol. 205, pp. 107577-107577
Closed Access | Times Cited: 38
Rice mapping based on Sentinel-1 images using the coupling of prior knowledge and deep semantic segmentation network: A case study in Northeast China from 2019 to 2021
Pengliang Wei, Dengfeng Chai, Ran Huang, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 112, pp. 102948-102948
Open Access | Times Cited: 31
Large-Scale Rice Mapping Using Multi-Task Spatiotemporal Deep Learning and Sentinel-1 SAR Time Series
Zhixian Lin, Renhai Zhong, Xingguo Xiong, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 699-699
Open Access | Times Cited: 30
Winter Wheat Mapping Method Based on Pseudo-Labels and U-Net Model for Training Sample Shortage
Jianhua Zhang, Shucheng You, Aixia Liu, et al.
Remote Sensing (2024) Vol. 16, Iss. 14, pp. 2553-2553
Open Access | Times Cited: 6
Advancements in crop mapping through remote sensing: A comprehensive review of concept, data sources, and procedures over four decades
Iman Khosravi
Remote Sensing Applications Society and Environment (2025), pp. 101527-101527
Closed Access
An interactive and iterative method for crop mapping through crowdsourcing optimized field samples
Qiangyi Yu, Yulin Duan, Qingying Wu, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 122, pp. 103409-103409
Open Access | Times Cited: 9
A novel neural network model to achieve generality for diverse morphologies and crop science interpretability in rice biomass estimation
Tomoaki Yamaguchi, Keisuke Katsura
Computers and Electronics in Agriculture (2024) Vol. 218, pp. 108653-108653
Open Access | Times Cited: 3
Inter-Continental Transfer of Pre-Trained Deep Learning Rice Mapping Model and Its Generalization Ability
Lingbo Yang, Ran Huang, Jingcheng Zhang, et al.
Remote Sensing (2023) Vol. 15, Iss. 9, pp. 2443-2443
Open Access | Times Cited: 8
A Convolutional Neural Network Method for Rice Mapping Using Time-Series of Sentinel-1 and Sentinel-2 Imagery
MohammadReza Saadat, Seyd Teymoor Seydi, Mahdi Hasanlou, et al.
Agriculture (2022) Vol. 12, Iss. 12, pp. 2083-2083
Open Access | Times Cited: 10
Automated rice mapping using multitemporal Sentinel-1 SAR imagery using dynamic threshold and slope-based index methods
Aishwarya Hegde A., Pruthviraj Umesh, Mohit P. Tahiliani
Remote Sensing Applications Society and Environment (2024), pp. 101410-101410
Closed Access | Times Cited: 1
An unsupervised semantic segmentation method that combines the ImSE-Net model with SLICm superpixel optimization
Zenan Yang, Haipeng Niu, Xiaoxuan Wang, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 1
A novel approach: Coupling prior knowledge and deep learning methods for large-scale plastic greenhouse extraction using Sentinel-1/2 data
Chang Zhou, Jingfeng Huang, Yuanjun Xiao, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 132, pp. 104073-104073
Open Access | Times Cited: 1
A review of paddy rice mapping with remote sensing technology
Xinyi Gao, Hong Chi, Jinliang Huang, et al.
National Remote Sensing Bulletin (2023), pp. 1-27
Open Access | Times Cited: 2
Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery
Li Sheng, Y.F. Lv, Zhouqiao Ren, et al.
Remote Sensing (2024) Vol. 17, Iss. 1, pp. 57-57
Open Access
Sub-national scale mapping of individual olive trees integrating Earth observation and deep learning
Chenxi Lin, Junxiong Zhou, Leikun Yin, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 217, pp. 18-31
Closed Access
R-Unet: A Deep Learning Model for Rice Extraction in Rio Grande do Sul, Brazil
Tingyan Fu, Shufang Tian, Jia Ge
Remote Sensing (2023) Vol. 15, Iss. 16, pp. 4021-4021
Open Access | Times Cited: 1
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