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Li Zhu et al.
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Quoc Cuong Tran et al.
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Sunil Saha et al.
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Xudong Hu et al.
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Markus Reichstein et al.
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Yufei Liu et al.
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Li Peng et al.
CLIMATE AND DEVELOPMENT (2019)
Advanced wind speed prediction using convective weather variables through machine learning application
Bhuiyan Md Abul Ehsan et al.
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A review of statistically-based landslide susceptibility models
Paola Reichenbach et al.
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Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches
Bahram Choubin et al.
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Binh Thai Pham et al.
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Semi-Supervised Deep Learning Using Pseudo Labels for Hyperspectral Image Classification
Hao Wu et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)
Clustering Millions of Faces by Identity
Charles Otto et al.
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Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China
Wei Chen et al.
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Yu-Dong Zhang et al.
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Abdelaziz Merghadi et al.
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Faming Huang et al.
GEOMATICS NATURAL HAZARDS & RISK (2018)
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Anuraganand Sharma
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B. Ravi Kiran et al.
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Deep Neural Network Self-training Based on Unsupervised Learning and Dropout
Hye-Woo Lee et al.
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Dieu Tien Bui et al.
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Di Wu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2016)
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Mahyat Shafapour Tehrany et al.
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Haoyuan Hong et al.
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Deep learning in neural networks: An overview
Juergen Schmidhuber
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An approach to reduce mapping errors in the production of landslide inventory maps
M. Santangelo et al.
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Effect of separate sampling on classification accuracy
Mohammad Shahrokh Esfahani et al.
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Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy)
Massimo Conforti et al.
CATENA (2014)
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Racha Elkadiri et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2014)
Semi-Supervised and Unsupervised Extreme Learning Machines
Gao Huang et al.
IEEE TRANSACTIONS ON CYBERNETICS (2014)
A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
Biswajeet Pradhan
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Active deep learning method for semi-supervised sentiment classification
Shusen Zhou et al.
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Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues
F. Catani et al.
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Landslide inventory maps: New tools for an old problem
Fausto Guzzetti et al.
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Geoffrey Hinton et al.
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Semi-Supervised Hashing for Large-Scale Search
Jun Wang et al.
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A generalized Hosmer-Lemeshow goodness-of-fit test for multinomial logistic regression models
Morten W. Fagerland et al.
STATA JOURNAL (2012)
Physical vulnerability assessment for alpine hazards: state of the art and future needs
M. Papathoma-Koehle et al.
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Generalizing a nonlinear geophysical flood theory to medium-sized river networks
Vijay K. Gupta et al.
GEOPHYSICAL RESEARCH LETTERS (2010)
Data clustering: 50 years beyond K-means
Anil K. Jain
PATTERN RECOGNITION LETTERS (2010)
The Wilcoxon-Mann-Whitney test under scrutiny
Morten W. Fagerland et al.
STATISTICS IN MEDICINE (2009)
The rainfall intensity-duration control of shallow landslides and debris flows: an update
Fausto Guzzetti et al.
LANDSLIDES (2008)
A caution regarding rules of thumb for variance inflation factors
Robert M. O'Brien
QUALITY & QUANTITY (2007)
Semi-supervised graph-based hyperspectral image classification
Gustavo Camps-Valls et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2007)
Landslide hazard and risk zonation - why is it still so difficult?
C. J. van Westen et al.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2006)
Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications
L Ayalew et al.
ENGINEERING GEOLOGY (2005)
Semi-supervised learning on Riemannian manifolds
M Belkin et al.
MACHINE LEARNING (2004)
A new criterion using information gain for action selection strategy in reinforcement learning
K Iwata et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2004)
Areas beneath the relative operating characteristics (ROC) and relative operating levels (ROL) curves: Statistical significance and interpretation
SJ Mason et al.
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY (2002)
Landslide risk assessment and management: an overview
FC Dai et al.
ENGINEERING GEOLOGY (2002)
Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach
M Ercanoglu et al.
ENVIRONMENTAL GEOLOGY (2002)
Landslide triggering by rain infiltration
RM Iverson
WATER RESOURCES RESEARCH (2000)