Qiang Zhang (0000-0002-7116-9327)

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I work in the field of remote sensing information processing, computer vision, and machine learning. Currently, I specifically focus on the following research topics:
- Remote Sensing Information Processing: Hyperspectral/Multitemporal/Ocean Remote Sensing
- Computer Vision: Image Denoising/Enhancement/Fusion/Super-Resolution, Low-level Vision
- Machine Learning: Deep Learning, Low-Rank Tensor Representation, Model-Data-Driven
Email: qzhang95@dlmu.edu.cn

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Dalian Maritime University: Dalian, CN

2022-07-20 to present | Associate Professor (Information Science and Technology College)

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Qiang Zhang

https://orcid.org/0000-0002-7116-9327

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Employment (1)

Dalian Maritime University: Dalian, CN

Education and qualifications (3)

Wuhan University: Wuhan, Hubei, CN

Wuhan University: Wuhan, Hubei, CN

Wuhan University: Wuhan, Hubei, CN

Works (29)

Dual-Intervention-Constrained Mask-Adversary Framework for Unsupervised Domain Adaptation of Hyperspectral Image Classification

Feedback Band Group and Variation Low-Rank Sparse Model for Hyperspectral Image Anomaly Detection

Frequency-Temporal Attention Network for Remote Sensing Imagery Change Detection

GACNet: Generate Adversarial-Driven Cross-Aware Network for Hyperspectral Wheat Variety Identification

Hyperspectral Image Denoising: From Model-Driven, Data-Driven, to Model-Data-Driven

Local Extremum Constrained Total Variation Model for Natural and Hyperspectral Image Non-Blind Deblurring

Thermal Infrared Hyperspectral Band Selection via Graph Neural Network for Land Surface Temperature Retrieval

Three-Dimension Spatial–Spectral Attention Transformer for Hyperspectral Image Denoising

Unseen Feature Extraction: Spatial Mapping Expansion With Spectral Compression Network for Hyperspectral Image Classification

Combined Deep Priors With Low-Rank Tensor Factorization for Hyperspectral Image Restoration

Deep Blind Super-Resolution for Satellite Video

Hyperspectral Denoising via Global Variation and Local Structure Low-Rank Model

Hyperspectral Image Classification Based on Interactive Transformer and CNN With Multilevel Feature Fusion Network

Beyond being wise after the event: Combining spatial, temporal and spectral information for Himawari-8 early-stage wildfire detection

Cooperated Spectral Low-Rankness Prior and Deep Spatial Prior for HSI Unsupervised Denoising

Robust Thick Cloud Removal for Multitemporal Remote Sensing Images Using Coupled Tensor Factorization

SSTNet: Spatial, Spectral, and Texture Aware Attention Network Using Hyperspectral Image for Corn Variety Identification

SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022

Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer

SGD-SM 2.0: An Improved Seamless Global Daily Soil Moisture Long-term Dataset From 2002 to 2022

Combined deep prior with low-rank tensor SVD for thick cloud removal in multitemporal images

Generating seamless global daily AMSR2 soil moisture (SGD-SM) long-term products for the years 2013–2019

SGD-SM: Generating Seamless Global Daily AMSR2 Soil Moisture Long-term Productions (2013–2019)

Deep spatio-spectral Bayesian posterior for hyperspectral image non-i.i.d. noise removal

Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning

Hybrid Noise Removal in Hyperspectral Imagery With a Spatial–Spectral Gradient Network

Hyperspectral Image Denoising Employing a Spatial–Spectral Deep Residual Convolutional Neural Network

Missing Data Reconstruction in Remote Sensing Image With a Unified Spatial–Temporal–Spectral Deep Convolutional Neural Network

Learning a Dilated Residual Network for SAR Image Despeckling

Peer review (3 reviews for 2 publications/grants)