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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.

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Showing 1-25 of 44 citing articles:

A comprehensive review of deep learning applications in hydrology and water resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
Water Science & Technology (2020) Vol. 82, Iss. 12, pp. 2635-2670
Open Access | Times Cited: 403
Deep learning for geological hazards analysis: Data, models, applications, and opportunities
Zhengjing Ma, Gang Mei
Earth-Science Reviews (2021) Vol. 223, pp. 103858-103858
Open Access | Times Cited: 200
Bayesian back analysis of unsaturated hydraulic parameters for rainfall-induced slope failure: A review
Haoqing Yang, Lulu Zhang
Earth-Science Reviews (2024) Vol. 251, pp. 104714-104714
Closed Access | Times Cited: 24
Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping
Emrehan Kutluğ Şahin
Geocarto International (2020) Vol. 37, Iss. 9, pp. 2441-2465
Closed Access | Times Cited: 120
Hybrid ensemble machine learning approaches for landslide susceptibility mapping using different sampling ratios at East Sikkim Himalayan, India
Sunil Saha, Jagabandhu Roy, Biswajeet Pradhan, et al.
Advances in Space Research (2021) Vol. 68, Iss. 7, pp. 2819-2840
Closed Access | Times Cited: 82
Slope Unit-Based Landslide Susceptibility Mapping Using Certainty Factor, Support Vector Machine, Random Forest, CF-SVM and CF-RF Models
Zhou Zhao, Zeng yuan Liu, Chong Xu
Frontiers in Earth Science (2021) Vol. 9
Open Access | Times Cited: 67
Landslide susceptibility mapping using CNN-1D and 2D deep learning algorithms: comparison of their performance at Asir Region, KSA
Ahmed M. Youssef, Biswajeet Pradhan, Abhirup Dikshit, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 4
Closed Access | Times Cited: 67
Predicting and Understanding Landslide Events With Explainable AI
Enrico Collini, Luciano Alessandro Ipsaro Palesi, Paolo Nesi, et al.
IEEE Access (2022) Vol. 10, pp. 31175-31189
Open Access | Times Cited: 44
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
EarthArXiv (California Digital Library) (2020)
Open Access | Times Cited: 56
Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India
Abhik Saha, Vasanta Govind Kumar Villuri, Ashutosh Bhardwaj
Land (2022) Vol. 11, Iss. 10, pp. 1711-1711
Open Access | Times Cited: 30
Enhanced Absence Sampling Technique for Data-Driven Landslide Susceptibility Mapping: A Case Study in Songyang County, China
Zijin Fu, Fawu Wang, Jie Dou, et al.
Remote Sensing (2023) Vol. 15, Iss. 13, pp. 3345-3345
Open Access | Times Cited: 17
Comparative study on landslide susceptibility mapping based on different ratios of training samples and testing samples by using RF and FR-RF models
Ke Xu, Zhou Zhao, Wei Chen, et al.
Natural Hazards Research (2023) Vol. 4, Iss. 1, pp. 62-74
Open Access | Times Cited: 17
A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides
Biswajeet Pradhan, Maher Ibrahim Sameen, Husam A. H. Al-Najjar, et al.
Remote Sensing (2021) Vol. 13, Iss. 22, pp. 4521-4521
Open Access | Times Cited: 36
Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study
Angelina Ageenko, Lærke Christina Hansen, Kevin Lundholm Lyng, et al.
ISPRS International Journal of Geo-Information (2022) Vol. 11, Iss. 6, pp. 324-324
Open Access | Times Cited: 23
Evaluation of deep learning algorithms for landslide susceptibility mapping in an alpine-gorge area: a case study in Jiuzhaigou County
Di Wang, Ronghao Yang, Xiao Wang, et al.
Journal of Mountain Science (2023) Vol. 20, Iss. 2, pp. 484-500
Closed Access | Times Cited: 16
Exploring novel hybrid soft computing models for landslide susceptibility mapping in Son La hydropower reservoir basin
Nguyễn Văn Dũng, Nguyễn Minh Hiếu, Tran Van Phong, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1688-1714
Open Access | Times Cited: 15
Development of multiclass alternating decision trees based models for landslide susceptibility mapping
Binh Thai Pham, Abolfazl Jaafari, Dam Duc Nguyen, et al.
Physics and Chemistry of the Earth Parts A/B/C (2022) Vol. 128, pp. 103235-103235
Closed Access | Times Cited: 11
Credal-Decision-Tree-Based Ensembles for Spatial Prediction of Landslides
Jingyun Gui, Ignacio Pérez‐Rey, Miao Yao, et al.
Water (2023) Vol. 15, Iss. 3, pp. 605-605
Open Access | Times Cited: 6
Exploring evolutionary-tuned autoencoder-based architectures for fault diagnosis in a wind turbine gearbox
Samuel M. Gbashi, Obafemi O. Olatunji, Paul A. Adedeji, et al.
Smart Science (2024), pp. 1-21
Open Access | Times Cited: 2
Adapting sudden landslide identification product (SLIP) and detecting real-time increased precipitation (DRIP) algorithms to map rainfall-triggered landslides in Western Cameroon highlands (Central-Africa)
Alfred Homère Ngandam Mfondoum, Pauline Wokwenmendam Nguet, Jean Valéry Mefire Mfondoum, et al.
Geoenvironmental Disasters (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 13
Comparison between Machine Learning and Physical Models Applied to the Evaluation of Co-Seismic Landslide Hazard
José Carlos Román-Herrera, Martín Jesús Rodríguez-Peces, Julio Garzón-Roca
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8285-8285
Open Access | Times Cited: 5
A Study of Landslide Susceptibility Mapping using Machine Learning Approach
Amit Juyal, Sachin Sharma
2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) (2021), pp. 1523-1528
Closed Access | Times Cited: 12
Using Deep Learning to Formulate the Landslide Rainfall Threshold of the Potential Large-Scale Landslide
Jie‐Lun Chiang, Chia-Ming Kuo, Leila Fazeldehkordi
Water (2022) Vol. 14, Iss. 20, pp. 3320-3320
Open Access | Times Cited: 8
Spatial prediction of physical and chemical properties of soil using optical satellite imagery: a state-of-the-art hybridization of deep learning algorithm
Fatemeh Sadat Hosseini, Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 4
A holistic approach of remote sensing, GIS, and machine learning for shallow landslide susceptibility mapping in Gaganbawada region of Western Ghats, India
Abhijit S. Patil, Sachin S. Panhalkar
DELETED (2024)
Closed Access | Times Cited: 1
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