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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:

Detection and segmentation of loess landslides via satellite images: a two-phase framework
Huajin Li, Yusen He, Qiang Xu, et al.
Landslides (2022) Vol. 19, Iss. 3, pp. 673-686
Closed Access | Times Cited: 128

Showing 1-25 of 128 citing articles:

Automatic Detection of Coseismic Landslides Using a New Transformer Method
Xiaochuan Tang, Zihan Tu, Yu Wang, et al.
Remote Sensing (2022) Vol. 14, Iss. 12, pp. 2884-2884
Open Access | Times Cited: 80
A landslide extraction method of channel attention mechanism U-Net network based on Sentinel-2A remote sensing images
Hesheng Chen, Yi He, Lifeng Zhang, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 552-577
Open Access | Times Cited: 51
Deep Learning for Exploring Landslides with Remote Sensing and Geo-Environmental Data: Frameworks, Progress, Challenges, and Opportunities
Qi Zhang, Teng Wang
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1344-1344
Open Access | Times Cited: 21
Short-Term Wind Power Prediction via Spatial Temporal Analysis and Deep Residual Networks
Huajin Li
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 66
SCADA Data Based Wind Power Interval Prediction Using LUBE-Based Deep Residual Networks
Huajin Li
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 64
Fast Seismic Landslide Detection Based on Improved Mask R-CNN
Rao Fu, Jing He, Gang Liu, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3928-3928
Open Access | Times Cited: 54
Landslide identification using machine learning techniques: Review, motivation, and future prospects
S. Sreelakshmi, S. S. Vinod Chandra, E. Shaji
Earth Science Informatics (2022) Vol. 15, Iss. 4, pp. 2063-2090
Closed Access | Times Cited: 39
An Improved Faster R-CNN Method for Landslide Detection in Remote Sensing Images
Han Qin, Jizhou Wang, Xi Mao, et al.
Journal of Geovisualization and Spatial Analysis (2023) Vol. 8, Iss. 1
Closed Access | Times Cited: 34
Construction technologies and mechanical effects of the pipe-jacking crossing anchor-cable group in soft stratum
Jianyong Han, Jun Wang, Dongfeng Jia, et al.
Frontiers in Earth Science (2023) Vol. 10
Open Access | Times Cited: 32
Mechanical response and parametric analysis of a deep excavation structure overlying an existing subway station: A case study of the Beijing subway station expansion
Jianyong Han, Jun Wang, Cheng Cheng, et al.
Frontiers in Earth Science (2023) Vol. 10
Open Access | Times Cited: 26
Application of Artificial Intelligence and Remote Sensing for Landslide Detection and Prediction: Systematic Review
Stephen Akosah, Ivan Gratchev, Donghyun Kim, et al.
Remote Sensing (2024) Vol. 16, Iss. 16, pp. 2947-2947
Open Access | Times Cited: 9
Optimizing Geo-Hazard Response: LBE-YOLO’s Innovative Lightweight Framework for Enhanced Real-Time Landslide Detection and Risk Mitigation
Yingjie Du, Xiangyang Xu, Xuhui He
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 534-534
Open Access | Times Cited: 8
Regional landslide mapping model developed by a deep transfer learning framework using post-event optical imagery
Adel Asadi, Laurie G. Baise, Snehamoy Chatterjee, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2024) Vol. 18, Iss. 1, pp. 186-210
Closed Access | Times Cited: 8
Towards a Synergistic Progressive Ensemble Framework for Automatic Post-Earthquake Landslide Recognition and Susceptibility Assessment
Zilin Xiang, Jie Dou, Lele Zhang, et al.
Mathematical Geosciences (2025)
Closed Access | Times Cited: 1
Optimizing the Sample Selection of Machine Learning Models for Landslide Susceptibility Prediction Using Information Value Models in the Dabie Mountain Area of Anhui, China
Yanrong Liu, Zhongqiu Meng, Lei Zhu, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 1971-1971
Open Access | Times Cited: 21
A novel Dynahead-Yolo neural network for the detection of landslides with variable proportions using remote sensing images
Zheng Han, Zhenxiong Fang, Yange Li, et al.
Frontiers in Earth Science (2023) Vol. 10
Open Access | Times Cited: 20
Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information
Adel Asadi, Laurie G. Baise, Magaly Koch, et al.
Natural Hazards (2024) Vol. 120, Iss. 6, pp. 5163-5200
Closed Access | Times Cited: 7
Dynamic analyses of soil erosion and improved potential combining topography and socio-economic factors on the Loess Plateau
Shuang Yuan, Qiang Xu, Kuanyao Zhao, et al.
Ecological Indicators (2024) Vol. 160, pp. 111814-111814
Open Access | Times Cited: 7
Generative probabilistic prediction of precipitation induced landslide deformation with variational autoencoder and gated recurrent unit
Wencheng Cai, Fuan Lan, Xianhao Huang, et al.
Frontiers in Earth Science (2024) Vol. 12
Open Access | Times Cited: 6
DRs-UNet: A Deep Semantic Segmentation Network for the Recognition of Active Landslides from InSAR Imagery in the Three Rivers Region of the Qinghai–Tibet Plateau
Ximing Chen, Xin Yao, Zhenkai Zhou, et al.
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1848-1848
Open Access | Times Cited: 27
Hydrochemical Characteristics and Groundwater Quality Assessment Using an Integrated Approach of the PCA, SOM, and Fuzzy c-Means Clustering: A Case Study in the Northern Sichuan Basin
Rongwen Yao, Yuting Yan, Changli Wei, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 26
Sematic segmentation of loess landslides with STAPLE mask and fully connected conditional random field
Huajin Li, Yusen He, Qiang Xu, et al.
Landslides (2022) Vol. 20, Iss. 2, pp. 367-380
Closed Access | Times Cited: 24
Comparing Convolutional Neural Network and Machine Learning Models in Landslide Susceptibility Mapping: A Case Study in Wenchuan County
Sikui Zhang, Lin Bai, Yuanwei Li, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 21
Landslide susceptibility assessment using statistical and machine learning techniques: A case study in the upper reaches of the Minjiang River, southwestern China
Sixiang Ling, Siyuan Zhao, Junpeng Huang, et al.
Frontiers in Earth Science (2022) Vol. 10
Open Access | Times Cited: 20
Assessing landslide susceptibility based on the random forest model and multi-source heterogeneous data
Mengxia Li, Haiying Wang, Jinlong Chen, et al.
Ecological Indicators (2024) Vol. 158, pp. 111600-111600
Open Access | Times Cited: 4
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