Random-Drop Data Augmentation of Deep Convolutional Neural Network for Mineral Prospectivity Mapping
出版年份 2020 全文链接
标题
Random-Drop Data Augmentation of Deep Convolutional Neural Network for Mineral Prospectivity Mapping
作者
关键词
-
出版物
Natural Resources Research
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2020-09-12
DOI
10.1007/s11053-020-09742-z
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Data-Driven Predictive Modelling of Mineral Prospectivity Using Machine Learning and Deep Learning Methods: A Case Study from Southern Jiangxi Province, China
- (2020) Tao Sun et al. Minerals
- Effects of Random Negative Training Samples on Mineral Prospectivity Mapping
- (2020) Renguang Zuo et al. Natural Resources Research
- Geodata Science-Based Mineral Prospectivity Mapping: A Review
- (2020) Renguang Zuo Natural Resources Research
- Recognizing multivariate geochemical anomalies for mineral exploration by combining deep learning and one-class support vector machine
- (2020) Yihui Xiong et al. COMPUTERS & GEOSCIENCES
- Modeling of Cu-Au prospectivity in the Carajás mineral province (Brazil) through machine learning: Dealing with imbalanced training data
- (2020) Elias Martins Guerra Prado et al. ORE GEOLOGY REVIEWS
- Deep learning and its application in geochemical mapping
- (2019) Renguang Zuo et al. EARTH-SCIENCE REVIEWS
- Applications of deep convolutional neural networks in prospecting prediction based on two-dimensional geological big data
- (2019) Shi Li et al. NEURAL COMPUTING & APPLICATIONS
- Mapping Mineral Prospectivity via Semi-supervised Random Forest
- (2019) Jian Wang et al. Natural Resources Research
- Geodata science and geochemical mapping
- (2019) Renguang Zuo et al. JOURNAL OF GEOCHEMICAL EXPLORATION
- GIS-based rare events logistic regression for mineral prospectivity mapping
- (2018) Yihui Xiong et al. COMPUTERS & GEOSCIENCES
- Characterization and origin of granites from the Luoyang Fe deposit, southwestern Fujian Province, South China
- (2018) Zhen-Jie Zhang et al. JOURNAL OF GEOCHEMICAL EXPLORATION
- Effects of misclassification costs on mapping mineral prospectivity
- (2017) Yihui Xiong et al. ORE GEOLOGY REVIEWS
- Big Data Analytics of Identifying Geochemical Anomalies Supported by Machine Learning Methods
- (2017) Renguang Zuo et al. Natural Resources Research
- Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods
- (2017) Renguang Zuo Natural Resources Research
- Big Earth Data from space: a new engine for Earth science
- (2016) Huadong Guo et al. Science Bulletin
- The Fault Systerm of the North Section of Liaodong Salient, Constraints from Seismic Data and Physical Modeling Experiment
- (2015) Jing ZHANG et al. ACTA GEOLOGICA SINICA-ENGLISH EDITION
- Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines)
- (2015) Emmanuel John M. Carranza et al. COMPUTERS & GEOSCIENCES
- Rotation-invariant convolutional neural networks for galaxy morphology prediction
- (2015) Sander Dieleman et al. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
- Evaluation of uncertainty in mineral prospectivity mapping due to missing evidence: A case study with skarn-type Fe deposits in Southwestern Fujian Province, China
- (2015) Renguang Zuo et al. ORE GEOLOGY REVIEWS
- Receiver operating characteristics (ROC) as validation tool for prospectivity models — A magmatic Ni–Cu case study from the Central Lapland Greenstone Belt, Northern Finland
- (2015) Vesa Nykänen et al. ORE GEOLOGY REVIEWS
- A comparative study of fuzzy weights of evidence and random forests for mapping mineral prospectivity for skarn-type Fe deposits in the southwestern Fujian metallogenic belt, China
- (2015) ZhenJie Zhang et al. Science China-Earth Sciences
- Comparison of the Data-Driven Random Forests Model and a Knowledge-Driven Method for Mineral Prospectivity Mapping: A Case Study for Gold Deposits Around the Huritz Group and Nueltin Suite, Nunavut, Canada
- (2015) G. McKay et al. Natural Resources Research
- Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)
- (2015) Emmanuel John M. Carranza et al. Natural Resources Research
- Support vector machine for multi-classification of mineral prospectivity areas
- (2012) Maysam Abedi et al. COMPUTERS & GEOSCIENCES
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas
- (2012) Qiuming Cheng JOURNAL OF GEOCHEMICAL EXPLORATION
- Support vector machine: A tool for mapping mineral prospectivity
- (2010) Renguang Zuo et al. COMPUTERS & GEOSCIENCES
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now