Chunxia Zhang

Signal Process., 2022

A Novel Data Augmentation Method for Chinese Character Spatial Structure Recognition by Normalized Deformable Convolutional Networks.

[BibT_eX]

[DOI]

Sheng Zhuo

Neural Process. Lett., 2022

Seismic Data Reconstruction via Recurrent Residual Multiscale Inference.

[BibT_eX]

[DOI]

IEEE Geosci. Remote. Sens. Lett., 2022

A model-driven network for guided image denoising.

[BibT_eX]

[DOI]

Inf. Fusion, 2022

Seismic fault detection using convolutional neural networks with focal loss.

[BibT_eX]

[DOI]

Comput. Geosci., 2022

Forecasting stock volatility and value-at-risk based on temporal convolutional networks.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

MSSPN: Automatic First Arrival Picking using Multi-Stage Segmentation Picking Network.

[BibT_eX]

[DOI]

CoRR, 2022

Automatic Velocity Picking Using Unsupervised Ensemble Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation Network.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Global Context-Augmented Objection Detection in VHR Optical Remote Sensing Images.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2021

Pansharpening Via Neighbor Embedding of Spatial Details.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

MFIF-GAN: A new generative adversarial network for multi-focus image fusion.

[BibT_eX]

[DOI]

Signal Process. Image Commun., 2021

CondenseNet with exclusive lasso regularization.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2021

A novel method for Mandarin speech synthesis by inserting prosodic structure prediction into Tacotron2.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2021

DPP-VSE: Constructing a variable selection ensemble by determinantal point processes.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2021

Discrete Cosine Transform Network for Guided Depth Map Super-Resolution.

[BibT_eX]

[DOI]

CoRR, 2021

Empirical Evaluation on Utilizing CNN-features for Seismic Patch Classification.

[BibT_eX]

[DOI]

Xiaoli Wei

Sang-Woon Kim

Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

Deep Convolutional Sparse Coding Network For Pansharpening With Guidance Of Side Information.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Deep Gradient Projection Networks for Pan-sharpening.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Bayesian Transfer Learning for Object Detection in Optical Remote Sensing Images.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2020

HAM-MFN: Hyperspectral and Multispectral Image Multiscale Fusion Network With RAP Loss.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2020

Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy.

[BibT_eX]

[DOI]

IEEE Trans. Computational Imaging, 2020

Robust CP Tensor Factorization With Skew Noise.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2020

A distributed parallel training method of deep belief networks.

[BibT_eX]

[DOI]

Soft Comput., 2020

Bayesian fusion for infrared and visible images.

[BibT_eX]

[DOI]

Signal Process., 2020

PercepPan: Towards Unsupervised Pan-Sharpening Based on Perceptual Loss.

[BibT_eX]

[DOI]

Remote. Sens., 2020

PWNet: An Adaptive Weight Network for the Fusion of Panchromatic and Multispectral Images.

[BibT_eX]

[DOI]

Remote. Sens., 2020

Weighted-capsule routing via a fuzzy gaussian model.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2020

Adaptive quantile low-rank matrix factorization.

[BibT_eX]

[DOI]

Pattern Recognit., 2020

Bayesian deep matrix factorization network for multiple images denoising.

[BibT_eX]

[DOI]

Neural Networks, 2020

On selective learning in stochastic stepwise ensembles.

[BibT_eX]

[DOI]

Sang-Woon Kim

Int. J. Mach. Learn. Cybern., 2020

Variational Bayesian weighted complex network reconstruction.

[BibT_eX]

[DOI]

Inf. Sci., 2020

When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Convolutional Sparse Coding Networks for Image Fusion.

[BibT_eX]

[DOI]

CoRR, 2020

Efficient and Interpretable Infrared and Visible Image Fusion Via Algorithm Unrolling.

[BibT_eX]

[DOI]

CoRR, 2020

MFFW: A new dataset for multi-focus image fusion.

[BibT_eX]

[DOI]

CoRR, 2020

DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Spectral Learning Algorithm Reveals Propagation Capability of Complex Networks.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2019

Pruning variable selection ensembles.

[BibT_eX]

[DOI]

Yilei Wu

Mu Zhu

Stat. Anal. Data Min., 2019

Discriminative Representation Learning with Supervised Auto-encoder.

[BibT_eX]

[DOI]

Neural Process. Lett., 2019

Improving text classification with weighted word embeddings via a multi-channel TextCNN model.

[BibT_eX]

[DOI]

Neurocomputing, 2019

A novel variational Bayesian method for variable selection in logistic regression models.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2019

2018

Early stopping aggregation in selective variable selection ensembles for high-dimensional linear regression models.

[BibT_eX]

[DOI]

Qing-Yan Yin

Knowl. Based Syst., 2018

An effective hierarchical extreme learning machine based multimodal fusion framework.

[BibT_eX]

[DOI]

Neurocomputing, 2018

Variational Bayesian Complex Network Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2018

2017

A ranking-based strategy to prune variable selection ensembles.

[BibT_eX]

[DOI]

Qingyan Yin

Knowl. Based Syst., 2017

Graph-based discriminative concept factorization for data representation.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2017

A new regularized restricted Boltzmann machine based on class preserving.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2017

Generalized extreme learning machine autoencoder and a new deep neural network.

[BibT_eX]

[DOI]

Neurocomputing, 2017

A modified version of Helmholtz machine by using a Restricted Boltzmann Machine to model the generative probability of the top layer.

[BibT_eX]

[DOI]

Neurocomputing, 2017

Ensembling Variable Selectors by Stability Selection for the Cox Model.

[BibT_eX]

[DOI]

Qing-Yan Yin

Jun-Li Li

Comput. Intell. Neurosci., 2017

2016

Randomizing outputs to increase variable selection accuracy.

[BibT_eX]

[DOI]

Nan-Nan Ji

Neurocomputing, 2016

A new deep neural network based on a stack of single-hidden-layer feedforward neural networks with randomly fixed hidden neurons.

[BibT_eX]

[DOI]

Neurocomputing, 2016

PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection.

[BibT_eX]

[DOI]

Sang-Woon Kim

Comput. Stat., 2016

2015

Investigating the Effect of Randomly Selected Feature Subsets on Bagging and Boosting.

[BibT_eX]

[DOI]

Gao Guo

Commun. Stat. Simul. Comput., 2015

A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models.

[BibT_eX]

[DOI]

Proceedings of the Multiple Classifier Systems - 12th International Workshop, 2015

Building variable selection ensembles for linear regression models by adding noise.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, 2015

2014

Learning ensemble classifiers via restricted Boltzmann machines.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2014

Discriminative restricted Boltzmann machine for invariant pattern recognition with linear transformations.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2014

A sparse-response deep belief network based on rate distortion theory.

[BibT_eX]

[DOI]

Nan-Nan Ji

Pattern Recognit., 2014

Enhancing performance of restricted Boltzmann machines via log-sum regularization.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2014

IRUSRT: A Novel Imbalanced Learning Technique by Combining Inverse Random Under Sampling and Random Tree.

[BibT_eX]

[DOI]

Commun. Stat. Simul. Comput., 2014

Clustering with Prim's sequential representation of minimum spanning tree.

[BibT_eX]

[DOI]

Jian Zhuang

Appl. Math. Comput., 2014

Boosting variable selection algorithm for linear regression models.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Natural Computation, 2014

2012

Enhancing Spectral Unmixing by Local Neighborhood Weights.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2012

2011

An experimental study of one- and two-level classifier fusion for different sample sizes.

[BibT_eX]

[DOI]

Robert P. W. Duin

Pattern Recognit. Lett., 2011

2010

A variant of Rotation Forest for constructing ensemble classifiers.

[BibT_eX]

[DOI]

Pattern Anal. Appl., 2010

Out-of-Bag Estimation of the Optimal Hyperparameter in SubBag Ensemble Method.

[BibT_eX]

[DOI]

Gai-Ying Zhang

Commun. Stat. Simul. Comput., 2010

2009

A novel method for constructing ensemble classifiers.

[BibT_eX]

[DOI]

Stat. Comput., 2009

Using Boosting to prune Double-Bagging ensembles.

[BibT_eX]

[DOI]

Gai-Ying Zhang

Comput. Stat. Data Anal., 2009

An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets.

[BibT_eX]

[DOI]

Robert P. W. Duin

Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009

2008

RotBoost: A technique for combining Rotation Forest and AdaBoost.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2008

A local boosting algorithm for solving classification problems.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2008

An empirical study of using Rotation Forest to improve regressors.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2008

2007

An empirical study of a test for polynomial relationships in randomly right censored regression models.

[BibT_eX]

[DOI]

Chang-Lin Mei