305 citations · 440 across the 6 of their papers we have counts for
6 papers
Polarimetric SAR Image Semantic Segmentation with 3D Discrete Wavelet Transform and Markov Random Field
Haixia Bi, Lin Xu, Xiangyong Cao +2
Polarimetric synthetic aperture radar (PolSAR) image segmentation is currently of great importance in image processing for remote sensing applications. However, it is a challenging…
Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network
Xiangyong Cao, Feng Zhou, Lin Xu +3
This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian…
Greedy Criterion in Orthogonal Greedy Learning
Lin Xu, Shaobo Lin, Jinshan Zeng +2
Orthogonal greedy learning (OGL) is a stepwise learning scheme that starts with selecting a new atom from a specified dictionary via the steepest gradient descent (SGD) and then bu…
Re-scale AdaBoost for Attack Detection in Collaborative Filtering Recommender Systems
Zhihai Yang, Lin Xu, Zhongmin Cai
Collaborative filtering recommender systems (CFRSs) are the key components of successful e-commerce systems. Actually, CFRSs are highly vulnerable to attacks since its openness. Ho…
Re-scale boosting for regression and classification
Shaobo Lin, Yao Wang, Lin Xu
Boosting is a learning scheme that combines weak prediction rules to produce a strong composite estimator, with the underlying intuition that one can obtain accurate prediction rul…
Greedy metrics in orthogonal greedy learning
Lin Xu, Shaobo Lin, Jinshan Zeng +1
Orthogonal greedy learning (OGL) is a stepwise learning scheme that adds a new atom from a dictionary via the steepest gradient descent and build the estimator via orthogonal proje…