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:

Geochemical survey data cube: A useful tool for lithological classification and geochemical anomaly identification
Ying Xu, Renguang Zuo
Geochemistry (2023) Vol. 84, Iss. 2, pp. 125959-125959
Closed Access | Times Cited: 14

Showing 14 citing articles:

Geological Knowledge‐Guided Dual‐Branch Deep Learning Model for Identification of Geochemical Anomalies Related to Mineralization
Ying Xu, Renguang Zuo, Yang Bai
Journal of Geophysical Research Machine Learning and Computation (2025) Vol. 2, Iss. 1
Open Access | Times Cited: 2

A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration
Renguang Zuo, Ying Xu
Computers & Geosciences (2023) Vol. 182, pp. 105490-105490
Closed Access | Times Cited: 26

The graph attention network and its post-hoc explanation for recognizing mineralization-related geochemical anomalies
Ying Xu, Renguang Zuo, Gubin Zhang
Applied Geochemistry (2023) Vol. 155, pp. 105722-105722
Closed Access | Times Cited: 20

An interpretable attention branch convolutional neural network for identifying geochemical anomalies related to mineralization
Fanfan Yang, Renguang Zuo, Yihui Xiong, et al.
Journal of Geochemical Exploration (2023) Vol. 252, pp. 107274-107274
Closed Access | Times Cited: 14

Geologically constrained unsupervised dual-branch deep learning algorithm for geochemical anomalies identification
Ying Xu, Luyi Shi, Renguang Zuo
Applied Geochemistry (2024) Vol. 174, pp. 106137-106137
Closed Access | Times Cited: 5

Spatial-Spectrum Two-Branch Model Based on a Superpixel Graph Convolutional Network and 1DCNN for Geochemical Anomaly Identification
Ying Xu, Renguang Zuo
Mathematical Geosciences (2024) Vol. 57, Iss. 2, pp. 307-331
Closed Access | Times Cited: 4

Data-centric approach for predicting critical metals distribution: Heavy rare earth elements in cretaceous Mediterranean-type karst bauxite deposits, southern Italy
Roberto Buccione, Ouafi Ameur-Zaimeche, Abdelhamid Ouladmansour, et al.
Geochemistry (2023), pp. 126026-126026
Closed Access | Times Cited: 6

Geo-Hgan: Unsupervised anomaly detection in geochemical data via latent space learning
Liang Ding, Bainian Chen, Yuelong Zhu, et al.
Computers & Geosciences (2024) Vol. 192, pp. 105703-105703
Closed Access | Times Cited: 2

Graph convolutional network for lithological classification and mapping using stream sediment geochemical data and geophysical data
Fang Hao, Yue Liu, Qingteng Zhang
Geochemistry Exploration Environment Analysis (2024) Vol. 24, Iss. 2
Closed Access | Times Cited: 1

Mineral classification using convolutional neural networks and SWIR hyperspectral imaging
José Cifuentes, Luis Arias, Éric Pirard, et al.
(2024), pp. 17-17
Closed Access

“Critical Minerals: Current Perspectives”
Behnam Sadeghi, Simon M. Jowitt, Alok Porwal, et al.
Geochemistry (2024) Vol. 84, Iss. 2, pp. 126131-126131
Closed Access

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