Spectral–spatial residual network for hyperspectral image classification: A 3-D deep learning framework

Z Zhong, J Li, Z Luo, M Chapman - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
In this paper, we designed an end-to-end spectral-spatial residual network (SSRN) that
takes raw 3-D cubes as input data without feature engineering for hyperspectral image …
被引用次数：1440 相关文章

[引用][C] Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Z Zhong, J Li, Z Luo, M Chapman - IEEE Transactions on Geoscience …, 2018 - cir.nii.ac.jp
Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep
Learning Framework | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細 …

[引用][C] Spectral-Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Z Zhong, J Li, Z Luo… - IEEE Transactions on …, 2018 - ui.adsabs.harvard.edu
Spectral-Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning
Framework - NASA/ADS Now on home page ads icon ads Enable full ADS view NASA/ADS …
[PDF] researchgate.net

[PDF][PDF] Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Z Zhong, J Li, Z Luo, M Chapman - researchgate.net
In this paper, we designed an end-to-end spectral–spatial residual network (SSRN) that
takes raw 3-D cubes as input data without feature engineering for hyperspectral image …
[PDF] uwaterloo.ca

[PDF][PDF] Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

Z Zhong, J Li, Z Luo, M Chapman - IEEE TRANSACTIONS ON …, 2018 - uwaterloo.ca
In this paper, we designed an end-to-end spectral–spatial residual network (SSRN) that
takes raw 3-D cubes as input data without feature engineering for hyperspectral image …