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2020 – today
- 2024
[j12]Xikun Hu
, Hao Wen, Puzhao Zhang, Ka-Veng Yuen, Ping Zhong:
Near Real-Time Burned Area Progression Mapping With Multispectral Data Using Ensemble Learning. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024)- [j11]Puzhao Zhang, Xikun Hu, Yifang Ban, Andrea Nascetti, Maoguo Gong:
Assessing Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2 Data for Large-Scale Wildfire-Burned Area Mapping: Insights from the 2017-2019 Canada Wildfires. Remote. Sens. 16(3): 556 (2024) - [d1]Xikun Hu, Puzhao Zhang, Yifang Ban:
Large-scale burn severity mapping in multispectral imagery using deep semantic segmentation models. IEEE DataPort, 2024
- 2023
- [j10]Jiaxiang Huang, Puzhao Zhang:
Beyond Pixel-Wise Unmixing: Spatial-Spectral Attention Fully Convolutional Networks for Abundance Estimation. Remote. Sens. 15(24): 5694 (2023) - [j9]Yuxi Sun, Yunming Ye, Jian Kang, Rubén Fernández-Beltran, Shanshan Feng, Xutao Li, Chuyao Luo, Puzhao Zhang, Antonio Plaza:
Cross-View Object Geo-Localization in a Local Region With Satellite Imagery. IEEE Trans. Geosci. Remote. Sens. 61: 1-16 (2023) - [c7]Puzhao Zhang, Yifang Ban:
Unsupervised Geospatial Domain Adaptation for Large-Scale Wildfire Burned Area Mapping Using Sentinel-2 MSI and Sentinel-1 SAR Data. IGARSS 2023: 5742-5745 - 2022
- [c6]Xikun Hu, Puzhao Zhang, Yifang Ban:
Gan-based SAR to Optical Image Translation in Fire-Disturbed Regions. IGARSS 2022: 1456-1459 - [c5]Puzhao Zhang, Xikun Hu, Yifang Ban:
Wildfire-S1S2-Canada: A Large-Scale Sentinel-1/2 Wildfire Burned Area Mapping Dataset Based on the 2017-2019 Wildfires in Canada. IGARSS 2022: 7954-7957 - 2021
- [b1]Puzhao Zhang:
Deep Learning for Wildfire Progression Monitoring Using SAR and Optical Satellite Image Time Series ; Djupinlärning för övervakning av skogsbränders utveckling med hjälp av tidsserier av SAR- och optiska satellittidsserier. Royal Institute of Technology, Stockholm, Sweden, 2021 - 2020
- [j8]Tao Zhang, Puzhao Zhang, Weilin Zhong, Zhen Yang, Fan Yang:
JL-GFDN: A Novel Gabor Filter-Based Deep Network Using Joint Spectral-Spatial Local Binary Pattern for Hyperspectral Image Classification. Remote. Sens. 12(12): 2016 (2020)
2010 – 2019
- 2019
- [j7]Puzhao Zhang, Maoguo Gong, Hui Zhang, Jia Liu, Yifang Ban:
Unsupervised Difference Representation Learning for Detecting Multiple Types of Changes in Multitemporal Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 57(4): 2277-2289 (2019) - 2018
- [j6]Jia Liu, Maoguo Gong, A. Kai Qin, Puzhao Zhang:
A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images. IEEE Trans. Neural Networks Learn. Syst. 29(3): 545-559 (2018) - [c4]Can Qin, Maoguo Gong, Yue Wu, Dayong Tian, Puzhao Zhang:
Efficient Scene Labeling via Sparse Annotations. AAAI Workshops 2018: 194-201 - 2017
- [j5]Maoguo Gong, Xudong Niu, Puzhao Zhang, Zhetao Li:
Generative Adversarial Networks for Change Detection in Multispectral Imagery. IEEE Geosci. Remote. Sens. Lett. 14(12): 2310-2314 (2017) - [j4]Linzhi Su, Maoguo Gong, Puzhao Zhang, Mingyang Zhang, Jia Liu, Hailun Yang:
Deep learning and mapping based ternary change detection for information unbalanced images. Pattern Recognit. 66: 213-228 (2017) - [j3]Maoguo Gong, Tao Zhan, Puzhao Zhang, Qiguang Miao:
Superpixel-Based Difference Representation Learning for Change Detection in Multispectral Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 55(5): 2658-2673 (2017) - [c3]Puzhao Zhang, Maoguo Gong, Hui Zhang, Jia Liu:
DRLnet: Deep Difference Representation Learning Network and An Unsupervised Optimization Framework. IJCAI 2017: 3413-3419 - 2016
- [j2]Hui Zhang, Maoguo Gong, Puzhao Zhang, Linzhi Su, Jiao Shi:
Feature-Level Change Detection Using Deep Representation and Feature Change Analysis for Multispectral Imagery. IEEE Geosci. Remote. Sens. Lett. 13(11): 1666-1670 (2016) - [j1]Maoguo Gong, Puzhao Zhang, Linzhi Su, Jia Liu:
Coupled Dictionary Learning for Change Detection From Multisource Data. IEEE Trans. Geosci. Remote. Sens. 54(12): 7077-7091 (2016) - [c2]Wenping Ma, Zhizhou Li, Puzhao Zhang, Tianyu Hu:
DNN-Based Joint Classification for Multi-source Image Change Detection. BIC-TA (1) 2016: 425-430 - [c1]Linzhi Su, Jiao Shi, Puzhao Zhang, Zhao Wang, Maoguo Gong:
Detecting multiple changes from multi-temporal images by using stacked denosing autoencoder based change vector analysis. IJCNN 2016: 1269-1276
Coauthor Index
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