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Lian-Zhi Huo
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2020 – today
- 2022
- [j13]Libin Jiao, Lianzhi Huo, Changmiao Hu, Ping Tang, Zheng Zhang
:
Refined UNet V4: End-to-End Patch-Wise Network for Cloud and Shadow Segmentation with Bilateral Grid. Remote. Sens. 14(2): 358 (2022) - 2021
- [j12]Libin Jiao
, Lianzhi Huo, Changmiao Hu, Ping Tang:
Refined UNet v3: Efficient end-to-end patch-wise network for cloud and shadow segmentation with multi-channel spectral features. Neural Networks 143: 767-782 (2021) - [j11]Libin Jiao
, Chang-Miao Hu, Lian-Zhi Huo
, Ping Tang:
Guided-Pix2Pix: End-to-End Inference and Refinement Network for Image Dehazing. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 3052-3069 (2021) - [c7]Shujun Li, Lianzhi Huo:
Remote Sensing Image Change Detection Based on Fully Convolutional Network With Pyramid Attention. IGARSS 2021: 4352-4355 - 2020
- [j10]Chang-Miao Hu
, Lian-Zhi Huo
, Zheng Zhang
, Ping Tang
:
Multi-Temporal Landsat Data Automatic Cloud Removal Using Poisson Blending. IEEE Access 8: 46151-46161 (2020) - [j9]Libin Jiao, Lian-Zhi Huo, Chang-Miao Hu, Ping Tang:
Refined UNet: UNet-Based Refinement Network for Cloud and Shadow Precise Segmentation. Remote. Sens. 12(12): 2001 (2020) - [j8]Libin Jiao, Lian-Zhi Huo, Chang-Miao Hu, Ping Tang:
Refined UNet V2: End-to-End Patch-Wise Network for Noise-Free Cloud and Shadow Segmentation. Remote. Sens. 12(21): 3530 (2020) - [j7]Yuan Yuan
, Lei Lin
, Lian-Zhi Huo
, Yun-long Kong, Zengguang Zhou, Bin Wu
, Yan Jia:
Using An Attention-Based LSTM Encoder-Decoder Network for Near Real-Time Disturbance Detection. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 1819-1832 (2020)
2010 – 2019
- 2019
- [j6]Lian-Zhi Huo
, Luigi Boschetti
, Aaron M. Sparks
:
Object-Based Classification of Forest Disturbance Types in the Conterminous United States. Remote. Sens. 11(5): 477 (2019) - [c6]Chang-Miao Hu, Lian-Zhi Huo, Zheng Zhang, Ping Tang:
Automatic Cloud Removal from Multi-Temporal Landsat Collection 1 Data Using Poisson Blending. IGARSS 2019: 1661-1664 - 2018
- [j5]Lian-Zhi Huo, Ping Tang:
A graph-based active learning method for classification of remote sensing images. Int. J. Wavelets Multiresolution Inf. Process. 16(4): 1850023:1-1850023:16 (2018) - 2016
- [c5]Lian-Zhi Huo, Li-Jun Zhao, Ping Tang:
Hyperspectral image classification with sparse representation classifier and active learning. WHISPERS 2016: 1-5 - 2015
- [j4]Lian-Zhi Huo
, Ping Tang, Zheng Zhang, Devis Tuia
:
Semisupervised Classification of Remote Sensing Images With Hierarchical Spatial Similarity. IEEE Geosci. Remote. Sens. Lett. 12(1): 150-154 (2015) - 2014
- [j3]Zheng Zhang, Ping Tang, Lian-Zhi Huo, Zengguang Zhou:
MODIS NDVI time series clustering under dynamic time warping. Int. J. Wavelets Multiresolution Inf. Process. 12(5) (2014) - [j2]Lian-Zhi Huo
, Ping Tang:
A Batch-Mode Active Learning Algorithm Using Region-Partitioning Diversity for SVM Classifier. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(4): 1036-1046 (2014) - [j1]Li-Jun Zhao, Ping Tang, Lian-Zhi Huo
:
Land-Use Scene Classification Using a Concentric Circle-Structured Multiscale Bag-of-Visual-Words Model. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(12): 4620-4631 (2014) - [c4]Lian-Zhi Huo, Zheng Zhang, Liang Tang:
Critical class sensitive active learning method for classification of remote sensing imagery. DSAA 2014: 258-262 - [c3]Lian-Zhi Huo, Li-Jun Zhao, Ping Tang:
A novel semisupervised transductive SVM with spatial similarity for classification of hyperspectral data. WHISPERS 2014: 1-4 - 2011
- [c2]Lian-Zhi Huo, Ping Tang, Hong-Gan Wu:
Object oriented classification of high spatial imagery using Gabor textures and composite kernels. IGARSS 2011: 475-478 - [c1]Lian-Zhi Huo, Ping Tang:
Spectral and spatial classification of hyperspectral data using SVMs and Gabor textures. IGARSS 2011: 1708-1711
Coauthor Index

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