Assessment of Landslide Susceptibility Combining Deep Learning with Semi-Supervised Learning in Jiaohe County, Jilin Province, China

Collaborative learning of lightweight convolutional neural network and deep clustering for hyperspectral image semi-supervised classification with limited training samples

(2020) Bei Fang et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning

(2020) Jie Dou et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models

(2020) Zhilu Chang et al.   Remote Sensing

Mapping Landslides on EO Data: Performance of Deep Learning Models vs. Traditional Machine Learning Models

(2020) Nikhil Prakash et al.   Remote Sensing

Quantifying Uncertainty in Machine Learning-Based Power Outage Prediction Model Training: A Tool for Sustainable Storm Restoration

(2020) Feifei Yang et al.   Sustainability

Effectiveness assessment of Keras based deep learning with different robust optimization algorithms for shallow landslide susceptibility mapping at tropical area

(2020) Viet-Ha Nhu et al.   CATENA

Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment

(2020) Dieu Tien Bui et al.   CATENA

A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

(2020) Dong Van Dao et al.   CATENA

Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network

(2020) Li Zhu et al.   SENSORS

Robust Semi-Supervised Traffic Sign Recognition via Self-Training and Weakly-Supervised Learning

(2020) Obed Tettey Nartey et al.   SENSORS

Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm: A Case Study in the Nam Dam Commune, Vietnam

(2020) Quoc Cuong Tran et al.   Applied Sciences-Basel

Evaluating the Performance of Individual and Novel Ensemble of Machine Learning and Statistical Models for Landslide Susceptibility Assessment at Rudraprayag District of Garhwal Himalaya

(2020) Sunil Saha et al.   Applied Sciences-Basel

Landslide Susceptibility Mapping Using the Stacking Ensemble Machine Learning Method in Lushui, Southwest China

(2020) Xudong Hu et al.   Applied Sciences-Basel

Wasserstein GAN-Based Small-Sample Augmentation for New-Generation Artificial Intelligence: A Case Study of Cancer-Staging Data in Biology

(2019) Yufei Liu et al.   Engineering

The Application of a Three-Dimensional Deterministic Model in the Study of Debris Flow Prediction Based on the Rainfall-Unstable Soil Coupling Mechanism

(2019) Shuangshuang Qiao et al.   Processes

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

Semi-supervised deep learning of brain tissue segmentation

(2019) Ryo Ito et al.   NEURAL NETWORKS

Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment

(2019) Maher Ibrahim Sameen et al.   CATENA

A review of statistically-based landslide susceptibility models

(2018) Paola Reichenbach et al.   EARTH-SCIENCE REVIEWS

Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches

(2018) Bahram Choubin et al.   Environmental Earth Sciences

Bagging based Support Vector Machines for spatial prediction of landslides

(2018) Binh Thai Pham et al.   Environmental Earth Sciences

Semi-Supervised Deep Learning Using Pseudo Labels for Hyperspectral Image Classification

(2018) Hao Wu et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Clustering Millions of Faces by Identity

(2018) Charles Otto et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China

(2018) Wei Chen et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Multiple sclerosis identification by convolutional neural network with dropout and parametric ReLU

(2018) Yu-Dong Zhang et al.   Journal of Computational Science

Landslide Susceptibility Assessment at Mila Basin (Algeria): A Comparative Assessment of Prediction Capability of Advanced Machine Learning Methods

(2018) Abdelaziz Merghadi et al.   ISPRS International Journal of Geo-Information

Landslide susceptibility assessment in the Nantian area of China: a comparison of frequency ratio model and support vector machine

(2018) Faming Huang et al.   Geomatics Natural Hazards & Risk

Guided Stochastic Gradient Descent Algorithm for inconsistent datasets

(2018) Anuraganand Sharma   APPLIED SOFT COMPUTING

A Novel Hybrid Approach of Landslide Susceptibility Modeling Using Rotation Forest Ensemble and Different Base Classifiers

(2018) Binh Thai Pham et al.   Geocarto International

Using deep neural network with small dataset to predict material defects

(2018) Shuo Feng et al.   MATERIALS & DESIGN

Assessment of urban flood susceptibility using semi-supervised machine learning model

(2018) Gang Zhao et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Tumor gene expression data classification via sample expansion-based deep learning

(2017) Jian Liu et al.   Oncotarget

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition

(2016) Di Wu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Flood susceptibility assessment using GIS-based support vector machine model with different kernel types

(2015) Mahyat Shafapour Tehrany et al.   CATENA

Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines

(2015) Haoyuan Hong et al.   CATENA

Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree

(2015) Dieu Tien Bui et al.   Landslides

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

A Remote Sensing-Based Approach for Debris-Flow Susceptibility Assessment Using Artificial Neural Networks and Logistic Regression Modeling

(2014) Racha Elkadiri et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Semi-Supervised and Unsupervised Extreme Learning Machines

(2014) Gao Huang et al.   IEEE Transactions on Cybernetics

Effect of separate sampling on classification accuracy

(2013) Mohammad Shahrokh Esfahani et al.   BIOINFORMATICS

Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy)

(2013) Massimo Conforti et al.   CATENA

Active deep learning method for semi-supervised sentiment classification

(2013) Shusen Zhou et al.   NEUROCOMPUTING

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

(2012) Biswajeet Pradhan   COMPUTERS & GEOSCIENCES

Landslide inventory maps: New tools for an old problem

(2012) Fausto Guzzetti et al.   EARTH-SCIENCE REVIEWS

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

Semi-Supervised Hashing for Large-Scale Search

(2012) Jun Wang et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Generalizing a nonlinear geophysical flood theory to medium-sized river networks

(2010) Vijay K. Gupta et al.   GEOPHYSICAL RESEARCH LETTERS

Physical vulnerability assessment for alpine hazards: state of the art and future needs

(2010) M. Papathoma-Köhle et al.   NATURAL HAZARDS

Data clustering: 50 years beyond K-means

(2009) Anil K. Jain   PATTERN RECOGNITION LETTERS

The Wilcoxon-Mann-Whitney test under scrutiny

(2009) Morten W. Fagerland et al.   STATISTICS IN MEDICINE