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20172020
most citedExtreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

36 citations · 86 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20201 cited

NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image

Boaz Arad, Radu Timofte, Ohad Ben-Shahar +4

This paper reviews the second challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. As…

cs.CV20198 cited

SR-GAN: Semantic Rectifying Generative Adversarial Network for Zero-shot Learning

Zihan Ye, Fan Lyu, Linyan Li +3

The existing Zero-Shot learning (ZSL) methods may suffer from the vague class attributes that are highly overlapped for different classes. Unlike these methods that ignore the disc…

cs.CV201725 cited

Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image

Faxian Cao, Zhijing Yang, Jinchang Ren +2

As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral im…

cs.CV201716 cited

Does Normalization Methods Play a Role for Hyperspectral Image Classification?

Faxian Cao, Zhijing Yang, Jinchang Ren +2

For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will…

cs.CV201736 cited

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

Faxian Cao, Zhijing Yang, Jinchang Ren +1

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional feature…