Search Results for author: Liangpei Zhang

Found 74 papers, 32 papers with code

Revolutionizing Agrifood Systems with Artificial Intelligence: A Survey

no code implementations3 May 2023 Tao Chen, Liang Lv, Di Wang, Jing Zhang, Yue Yang, Zeyang Zhao, Chen Wang, Xiaowei Guo, Hao Chen, Qingye Wang, Yufei Xu, Qiming Zhang, Bo Du, Liangpei Zhang, DaCheng Tao

With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages.

Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

2 code implementations3 May 2023 Di Wang, Jing Zhang, Bo Du, DaCheng Tao, Liangpei Zhang

The success of the Segment Anything Model (SAM) demonstrates the significance of data-centric machine learning.

Instance Segmentation object-detection +2

HKNAS: Classification of Hyperspectral Imagery Based on Hyper Kernel Neural Architecture Search

1 code implementation23 Apr 2023 Di Wang, Bo Du, Liangpei Zhang, DaCheng Tao

Recent neural architecture search (NAS) based approaches have made great progress in hyperspectral image (HSI) classification tasks.

Neural Architecture Search

DCN-T: Dual Context Network with Transformer for Hyperspectral Image Classification

2 code implementations19 Apr 2023 Di Wang, Jing Zhang, Bo Du, Liangpei Zhang, DaCheng Tao

Hyperspectral image (HSI) classification is challenging due to spatial variability caused by complex imaging conditions.

Hyperspectral Image Classification Image Generation

GlobalMind: Global Multi-head Interactive Self-attention Network for Hyperspectral Change Detection

no code implementations18 Apr 2023 Meiqi Hu, Chen Wu, Liangpei Zhang

High spectral resolution imagery of the Earth's surface enables users to monitor changes over time in fine-grained scale, playing an increasingly important role in agriculture, defense, and emergency response.

Change Detection

Local-Global Temporal Difference Learning for Satellite Video Super-Resolution

1 code implementation10 Apr 2023 Yi Xiao, Qiangqiang Yuan, Kui Jiang, Xianyu Jin, Jiang He, Liangpei Zhang, Chia-Wen Lin

Optical-flow-based and kernel-based approaches have been widely explored for temporal compensation in satellite video super-resolution (VSR).

Optical Flow Estimation Video Super-Resolution

One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning

1 code implementation22 Mar 2023 Jingtao Li, Xinyu Wang, Shaoyu Wang, Hengwei Zhao, Liangpei Zhang, Yanfei Zhong

In this paper, an unsupervised transferred direct detection (TDD) model is proposed, which is optimized directly for the anomaly detection task (one-step paradigm) and has transferability.

Anomaly Detection

Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning

1 code implementation24 Oct 2022 Nan Xue, Tianfu Wu, Song Bai, Fu-Dong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr

At the core is a parsimonious representation that encodes a line segment using a closed-form 4D geometric vector, which enables lifting line segments in wireframe to an end-to-end trainable holistic attraction field that has built-in geometry-awareness, context-awareness and robustness.

Self-Supervised Learning Wireframe Parsing

Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model

2 code implementations8 Aug 2022 Di Wang, Qiming Zhang, Yufei Xu, Jing Zhang, Bo Du, DaCheng Tao, Liangpei Zhang

Large-scale vision foundation models have made significant progress in visual tasks on natural images, with vision transformers being the primary choice due to their good scalability and representation ability.

Aerial Scene Classification Few-Shot Learning +2

HyperNet: Self-Supervised Hyperspectral Spatial-Spectral Feature Understanding Network for Hyperspectral Change Detection

no code implementations20 Jul 2022 Meiqi Hu, Chen Wu, Liangpei Zhang

Only the positive samples at the same location of bi-temporal HSIs are created and forced to be aligned, aiming at learning the spectral difference-invariant features.

Change Detection Self-Supervised Learning

Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling

no code implementations6 Jan 2022 Yang Long, Gui-Song Xia, Liangpei Zhang, Gong Cheng, Deren Li

Finally, we perform ASP by unifying the tile-level scene classification and object-based image analysis to achieve pixel-wise semantic labeling.

Aerial Scene Classification Benchmarking +4

Self-Ensembling GAN for Cross-Domain Semantic Segmentation

1 code implementation15 Dec 2021 Yonghao Xu, Fengxiang He, Bo Du, DaCheng Tao, Liangpei Zhang

In SE-GAN, a teacher network and a student network constitute a self-ensembling model for generating semantic segmentation maps, which together with a discriminator, forms a GAN.

Semantic Segmentation

Hidden Path Selection Network for Semantic Segmentation of Remote Sensing Images

no code implementations9 Dec 2021 Kunping Yang, Xin-Yi Tong, Gui-Song Xia, Weiming Shen, Liangpei Zhang

Targeting at depicting land covers with pixel-wise semantic categories, semantic segmentation in remote sensing images needs to portray diverse distributions over vast geographical locations, which is difficult to be achieved by the homogeneous pixel-wise forward paths in the architectures of existing deep models.

Semantic Segmentation

Binary Change Guided Hyperspectral Multiclass Change Detection

no code implementations8 Dec 2021 Meiqi Hu, Chen Wu, Bo Du, Liangpei Zhang

In this study, we proposed an unsupervised Binary Change Guided hyperspectral multiclass change detection Network (BCG-Net) for HMCD, which aims at boosting the multiclass change detection result and unmixing result with the mature binary change detection approaches.

Change Detection

An Integrated Framework for the Heterogeneous Spatio-Spectral-Temporal Fusion of Remote Sensing Images

no code implementations1 Sep 2021 Menghui Jiang, Huanfeng Shen, Jie Li, Liangpei Zhang

Images from many remote sensing satellites, including MODIS, Landsat-8, Sentinel-1, and Sentinel-2, are utilized in the experiments.

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion

no code implementations13 Aug 2021 Huanfeng Shen, Menghui Jiang, Jie Li, Chenxia Zhou, Qiangqiang Yuan, Liangpei Zhang

In this paper, we systematically investigate the coupling of model-driven and data-driven methods, which has rarely been considered in the remote sensing image restoration and fusion communities.

Image Restoration

Spectral-Spatial Global Graph Reasoning for Hyperspectral Image Classification

2 code implementations26 Jun 2021 Di Wang, Bo Du, Liangpei Zhang

To tackle these problems, in this paper, different from previous approaches, we perform the superpixel generation on intermediate features during network training to adaptively produce homogeneous regions, obtain graph structures, and further generate spatial descriptors, which are served as graph nodes.

Classification Hyperspectral Image Classification

Robust Self-Ensembling Network for Hyperspectral Image Classification

1 code implementation8 Apr 2021 Yonghao Xu, Bo Du, Liangpei Zhang

Since the collection of pixel-level annotations for HSI is laborious and time-consuming, developing algorithms that can yield good performance in the small sample size situation is of great significance.

Classification General Classification +1

Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery

no code implementations2 Mar 2021 Chen Wu, Sihan Zhu, Jiaqi Yang, Meiqi Hu, Bo Du, Liangpei Zhang, Lefei Zhang, Chengxi Han, Meng Lan

Considering that public transportation was mostly reduced or even forbidden, our results indicate that city lockdown policies are effective at limiting human transmission within cities.

Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing

no code implementations2 Mar 2021 Danfeng Hong, wei he, Naoto Yokoya, Jing Yao, Lianru Gao, Liangpei Zhang, Jocelyn Chanussot, Xiao Xiang Zhu

Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS).

Super-resolution-based Change Detection Network with Stacked Attention Module for Images with Different Resolutions

1 code implementation27 Feb 2021 Mengxi Liu, Qian Shi, Andrea Marinoni, Da He, Xiaoping Liu, Liangpei Zhang

The experimental results demonstrate the superiority of the proposed method, which not only outperforms all baselines -with the highest F1 scores of 87. 40% on the building change detection dataset and 92. 94% on the change detection dataset -but also obtains the best accuracies on experiments performed with images having a 4x and 8x resolution difference.

Change Detection Metric Learning +1

Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion

no code implementations4 Feb 2021 Dong Chu, Huanfeng Shen, Xiaobin Guan, Jing M. Chen, Xinghua Li, Jie Li, Liangpei Zhang

The applications of Normalized Difference Vegetation Index (NDVI) time-series data are inevitably hampered by cloud-induced gaps and noise.

Time Series Analysis

Hyperspectral Anomaly Change Detection Based on Auto-encoder

1 code implementation27 Oct 2020 Meiqi Hu, Chen Wu, Liangpei Zhang, Bo Du

In the ACDA model, two systematic auto-encoder (AE) networks are deployed to construct two predictors from two directions.

Change Detection

Non-local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

1 code implementation24 Oct 2020 wei he, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan zhang, Liangpei Zhang

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting.

Denoising Image Restoration

Semantic Change Detection with Asymmetric Siamese Networks

1 code implementation12 Oct 2020 Kunping Yang, Gui-Song Xia, Zicheng Liu, Bo Du, Wen Yang, Marcello Pelillo, Liangpei Zhang

Given two multi-temporal aerial images, semantic change detection aims to locate the land-cover variations and identify their change types with pixel-wise boundaries.

Change Detection Management

Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning

no code implementations8 Sep 2020 Sheng-Jie Liu, Qian Shi, Liangpei Zhang

Current hyperspectral image classification assumes that a predefined classification system is closed and complete, and there are no unknown or novel classes in the unseen data.

Classification General Classification +1

An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images

no code implementations26 Jun 2020 Chen Wu, Yinong Guo, HaoNan Guo, Jingwen Yuan, Lixiang Ru, Hongruixuan Chen, Bo Du, Liangpei Zhang

The significant reduction and recovery of traffic density indicates that the lockdown policy in Wuhan show effectiveness in controlling human transmission inside the city, and the city returned to normal after lockdown lift.

Anomaly Detection Time Series Analysis

On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID

1 code implementation22 Jun 2020 Yang Long, Gui-Song Xia, Shengyang Li, Wen Yang, Michael Ying Yang, Xiao Xiang Zhu, Liangpei Zhang, Deren Li

After reviewing existing benchmark datasets in the research community of RS image interpretation, this article discusses the problem of how to efficiently prepare a suitable benchmark dataset for RS image interpretation.

General Classification Image Classification +1

DSDANet: Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection

no code implementations16 Jun 2020 Hongruixuan Chen, Chen Wu, Bo Du, Liangpei Zhang

By optimizing the network parameters and kernel coefficients with the source labeled data and target unlabeled data, DSDANet can learn transferrable feature representation that can bridge the discrepancy between two domains.

Change Detection Domain Adaptation

Holistically-Attracted Wireframe Parsing

1 code implementation CVPR 2020 Nan Xue, Tianfu Wu, Song Bai, Fu-Dong Wang, Gui-Song Xia, Liangpei Zhang, Philip H. S. Torr

For computing line segment proposals, a novel exact dual representation is proposed which exploits a parsimonious geometric reparameterization for line segments and forms a holistic 4-dimensional attraction field map for an input image.

Line Segment Detection Wireframe Parsing

Learning Regional Attraction for Line Segment Detection

no code implementations18 Dec 2019 Nan Xue, Song Bai, Fu-Dong Wang, Gui-Song Xia, Tianfu Wu, Liangpei Zhang, Philip H. S. Torr

Given a line segment map, the proposed regional attraction first establishes the relationship between line segments and regions in the image lattice.

Line Segment Detection

Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network

2 code implementations18 Dec 2019 Chen Wu, Hongruixuan Chen, Bo Do, Liangpei Zhang

Based on the KPCA convolution, an unsupervised deep siamese KPCA convolutional mapping network (KPCA-MNet) is designed for binary and multi-class change detection.

Change Detection

Change Detection in Multi-temporal VHR Images Based on Deep Siamese Multi-scale Convolutional Networks

3 code implementations27 Jun 2019 Hongruixuan Chen, Chen Wu, Bo Du, Liangpei Zhang

Based on the unit two novel deep siamese convolutional neural networks, called as deep siamese multi-scale convolutional network (DSMS-CN) and deep siamese multi-scale fully convolutional network (DSMS-FCN), are designed for unsupervised and supervised change detection, respectively.

Change Detection

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, Applications, and Prospects

no code implementations19 Dec 2018 Tian-Zhu Xiang, Gui-Song Xia, Liangpei Zhang

We hope this paper will provide remote-sensing researchers an overall picture of recent UAV-based remote sensing developments and help guide the further research on this topic.

Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images

no code implementations3 Dec 2018 Bo Du, Lixiang Ru, Chen Wu, Liangpei Zhang

In recent years, deep network has shown its brilliant performance in many fields including feature extraction and projection.

Change Detection

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

1 code implementation1 Oct 2018 Qiang Zhang, Qiangqiang Yuan, Jie Li, Xin-Xin Liu, Huanfeng Shen, Liangpei Zhang

The existence of hybrid noise in hyperspectral images (HSIs) severely degrades the data quality, reduces the interpretation accuracy of HSIs, and restricts the subsequent HSIs applications.


Spatial-Spectral Fusion by Combining Deep Learning and Variation Model

no code implementations4 Sep 2018 Huanfeng Shen, Menghui Jiang, Jie Li, Qiangqiang Yuan, Yanchong Wei, Liangpei Zhang

In the field of spatial-spectral fusion, the model-based method and the deep learning (DL)-based method are state-of-the-art.

Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models

no code implementations16 Jul 2018 Xin-Yi Tong, Gui-Song Xia, Qikai Lu, Huanfeng Shen, Shengyang Li, Shucheng You, Liangpei Zhang

The main idea is to rely on deep neural networks for presenting the contextual information contained in different types of land-covers and propose a pseudo-labeling and sample selection scheme for improving the transferability of deep models.

Classification Domain Adaptation +6

Recent advances and opportunities in scene classification of aerial images with deep models

no code implementations4 Jun 2018 Fan Hu, Gui-Song Xia, Wen Yang, Liangpei Zhang

Scene classification is a fundamental task in interpretation of remote sensing images, and has become an active research topic in remote sensing community due to its important role in a wide range of applications.

Classification General Classification +1

Accurate Building Detection in VHR Remote Sensing Images using Geometric Saliency

no code implementations4 Jun 2018 Jin Huang, Gui-Song Xia, Fan Hu, Liangpei Zhang

This paper aims to address the problem of detecting buildings from remote sensing images with very high resolution (VHR).

Large-scale Land Cover Classification in GaoFen-2 Satellite Imagery

no code implementations4 Jun 2018 Xin-Yi Tong, Qikai Lu, Gui-Song Xia, Liangpei Zhang

Many significant applications need land cover information of remote sensing images that are acquired from different areas and times, such as change detection and disaster monitoring.

Change Detection Classification +2

AID++: An Updated Version of AID on Scene Classification

no code implementations3 Jun 2018 Pu Jin, Gui-Song Xia, Fan Hu, Qikai Lu, Liangpei Zhang

Aerial image scene classification is a fundamental problem for understanding high-resolution remote sensing images and has become an active research task in the field of remote sensing due to its important role in a wide range of applications.

Aerial Scene Classification Classification +2

Hyperspectral image classification via a random patches network

1 code implementation ISPRS Journal of Photogrammetry and Remote Sensing 2018 Yonghao Xu, Bo Du, Fan Zhang, Liangpei Zhang

Due to the remarkable achievements obtained by deep learning methods in the fields of computer vision, an increasing number of researches have been made to apply these powerful tools into hyperspectral image (HSI) classification.

Classification Few-Shot Image Classification +1

Learning the Synthesizability of Dynamic Texture Samples

no code implementations3 Feb 2018 Feng Yang, Gui-Song Xia, Dengxin Dai, Liangpei Zhang

In this paper, we investigate the synthesizability of dynamic texture samples: {\em given a dynamic texture sample, how synthesizable it is by using EDTS, and which EDTS method is the most suitable to synthesize it?}

regression Texture Synthesis

A Multi-Scale and Multi-Depth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening

no code implementations28 Dec 2017 Qiangqiang Yuan, Yancong Wei, Xiangchao Meng, Huanfeng Shen, Liangpei Zhang

Pan-sharpening is a fundamental and significant task in the field of remote sensing imagery processing, in which high-resolution spatial details from panchromatic images are employed to enhance the spatial resolution of multi-spectral (MS) images.

Deep learning in remote sensing: a review

1 code implementation11 Oct 2017 Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia, Liangpei Zhang, Feng Xu, Friedrich Fraundorfer

In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously simple to start with.

Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

no code implementations23 Jul 2017 Xin-Yi Tong, Gui-Song Xia, Fan Hu, Yanfei Zhong, Mihai Datcu, Liangpei Zhang

Over the past two decades, a large amount of research on this task has been carried out, which mainly focuses on the following three core issues: feature extraction, similarity metric and relevance feedback.

Image Retrieval Retrieval

Boosting the accuracy of multi-spectral image pan-sharpening by learning a deep residual network

no code implementations22 May 2017 Yancong Wei, Qiangqiang Yuan, Huanfeng Shen, Liangpei Zhang

In the field of fusing multi-spectral and panchromatic images (Pan-sharpening), the impressive effectiveness of deep neural networks has been recently employed to overcome the drawbacks of traditional linear models and boost the fusing accuracy.

Anisotropic-Scale Junction Detection and Matching for Indoor Images

no code implementations16 Mar 2017 Nan Xue, Gui-Song Xia, Xiang Bai, Liangpei Zhang, Weiming Shen

This paper presents a novel approach to junction detection and characterization that exploits the locally anisotropic geometries of a junction and estimates the scales of these geometries using an \emph{a contrario} model.

Junction Detection

A multi-task convolutional neural network for mega-city analysis using very high resolution satellite imagery and geospatial data

no code implementations26 Feb 2017 Fan Zhang, Bo Du, Liangpei Zhang

For the second target, a novel CNN-based universal framework is proposed to process the VHR satellite images and generate the land-use, urban density, and population distribution maps.

Image Stitching by Line-guided Local Warping with Global Similarity Constraint

no code implementations25 Feb 2017 Tian-Zhu Xiang, Gui-Song Xia, Xiang Bai, Liangpei Zhang

On one hand, the line features are integrated into a local warping model through a designed weight function.

Image Stitching

Texture Characterization by Using Shape Co-occurrence Patterns

no code implementations10 Feb 2017 Gui-Song Xia, Gang Liu, Xiang Bai, Liangpei Zhang

In contrast with existing works, the proposed method not only inherits the strong ability to depict geometrical aspects of textures and the high robustness to variations of imaging conditions from the shape-based method, but also provides a flexible way to consider shape relationships and to compute high-order statistics on the tree.

Texture Classification

A Spatial and Temporal Non-Local Filter Based Data Fusion

no code implementations22 Nov 2016 Qing Cheng, Huiqing Liu, Huanfeng Shen, Penghai Wu, Liangpei Zhang

The spatiotemporal data fusion technique is considered as a cost-effective way to obtain remote sensing data with both high spatial resolution and high temporal frequency, by blending observations from multiple sensors with different advantages or characteristics.

Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery

no code implementations17 Jun 2016 Zhiwei Li, Huanfeng Shen, Huifang Li, Gui-Song Xia, Paolo Gamba, Liangpei Zhang

In this paper, an automatic multi-feature combined (MFC) method is proposed for cloud and cloud shadow detection in GF-1 WFV imagery.

Cloud Detection Shadow Detection

Image stitching with perspective-preserving warping

no code implementations17 May 2016 Tian-Zhu Xiang, Gui-Song Xia, Liangpei Zhang

Image stitching algorithms often adopt the global transformation, such as homography, and work well for planar scenes or parallax free camera motions.

Image Stitching

Dense v.s. Sparse: A Comparative Study of Sampling Analysis in Scene Classification of High-Resolution Remote Sensing Imagery

no code implementations4 Feb 2015 Jingwen Hu, Gui-Song Xia, Fan Hu, Liangpei Zhang

The experimental results on two commonly used datasets show that dense sampling has the best performance among all the strategies but with high spatial and computational complexity, random sampling gives better or comparable results than other sparse sampling methods, like the sophisticated multi-scale key-point operators and the saliency-based methods which are intensively studied and commonly used recently.

Classification General Classification +2

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