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20172020
most citedBayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem

8 citations · 27 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV20203 cited

Low-Rank Matrix Recovery from Noise via an MDL Framework-based Atomic Norm

Anyong Qin, Lina Xian, Yongliang Yang +2

The recovery of the underlying low-rank structure of clean data corrupted with sparse noise/outliers is attracting increasing interest. However, in many low-level vision problems,…

cs.CV2020

Learning a Deep Part-based Representation by Preserving Data Distribution

Anyong Qin, Zhaowei Shang, Zhuolin Tan +2

Unsupervised dimensionality reduction is one of the commonly used techniques in the field of high dimensional data recognition problems. The deep autoencoder network which constrai…

cs.CV20194 cited

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images

Lefei Zhang, Qian Zhang, Bo Du +3

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature and morp…

cs.LG20198 cited

Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem

Yang Lu, Yiu-ming Cheung, Yuan Yan Tang

Recent studies have shown that imbalance ratio is not the only cause of the performance loss of a classifier in imbalanced data classification. In fact, other data factors, such as…

cs.CV20171 cited

Constrained Manifold Learning for Hyperspectral Imagery Visualization

Danping Liao, Yuntao Qian, Yuan Yan Tang

Displaying the large number of bands in a hyper- spectral image (HSI) on a trichromatic monitor is important for HSI processing and analysis system. The visualized image shall conv…

cs.CV20172 cited

Modal Regression based Atomic Representation for Robust Face Recognition

Yulong Wang, Yuan Yan Tang, Luoqing Li +1

Representation based classification (RC) methods such as sparse RC (SRC) have shown great potential in face recognition in recent years. Most previous RC methods are based on the c…