Search Results for author: Hongruixuan Chen

Found 17 papers, 11 papers with code

HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images

2 code implementations14 Apr 2024 Chengxi Han, Chen Wu, HaoNan Guo, Meiqi Hu, Hongruixuan Chen

Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the change detection (CD) task.

Ranked #15 on Change Detection on LEVIR-CD (using extra training data)

Change Detection

Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery

1 code implementation14 Apr 2024 Chengxi Han, Chen Wu, HaoNan Guo, Meiqi Hu, Jiepan Li, Hongruixuan Chen

The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks.

Change Detection

ChangeMamba: Remote Sensing Change Detection with Spatio-Temporal State Space Model

1 code implementation4 Apr 2024 Hongruixuan Chen, Jian Song, Chengxi Han, Junshi Xia, Naoto Yokoya

For the change decoder, which is available in all three architectures, we propose three spatio-temporal relationship modeling mechanisms, which can be naturally combined with the Mamba architecture and fully utilize its attribute to achieve spatio-temporal interaction of multi-temporal features, thereby obtaining accurate change information.

2D Semantic Segmentation Attribute +1

Deep learning for multi-label classification of coral conditions in the Indo-Pacific via underwater photogrammetry

1 code implementation9 Mar 2024 Xinlei Shao, Hongruixuan Chen, Kirsty Magson, Jiaqi Wang, Jian Song, Jundong Chen, Jun Sasaki

A dataset containing over 20, 000 high-resolution coral images of different health conditions and stressors was constructed based on the field survey.

Decision Making Ensemble Learning +1

Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)

no code implementations17 Jan 2024 Hongruixuan Chen, Jian Song, Naoto Yokoya

In this study, we explore unsupervised multimodal change detection between two key remote sensing data sources: optical high-resolution imagery and OpenStreetMap (OSM) data.

Change Detection Segmentation

Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange

1 code implementation1 Oct 2023 Hongruixuan Chen, Jian Song, Chen Wu, Bo Du, Naoto Yokoya

Change detection (CD) is a critical task in studying the dynamics of ecosystems and human activities using multi-temporal remote sensing images.

Change Detection Image Enhancement +1

SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detection

1 code implementation5 Sep 2023 Jian Song, Hongruixuan Chen, Naoto Yokoya

However, when it comes to remote sensing image processing, the creation of synthetic datasets becomes challenging due to the demand for larger-scale and more diverse 3D models.

Change Detection

Unsupervised Multimodal Change Detection Based on Structural Relationship Graph Representation Learning

1 code implementation3 Oct 2022 Hongruixuan Chen, Naoto Yokoya, Chen Wu, Bo Du

Subsequently, the similarity levels of two structural relationships are calculated from learned graph representations and two difference images are generated based on the similarity levels.

Change Detection Graph Representation Learning

Dual-Tasks Siamese Transformer Framework for Building Damage Assessment

no code implementations26 Jan 2022 Hongruixuan Chen, Edoardo Nemni, Sofia Vallecorsa, Xi Li, Chen Wu, Lars Bromley

Considering the frontier advances of Transformer architecture in the computer vision field, in this paper, we present the first attempt at designing a Transformer-based damage assessment architecture (DamFormer).

Disaster Response Extracting Buildings In Remote Sensing Images +1

Unsupervised Domain Adaptation for Semantic Segmentation via Low-level Edge Information Transfer

no code implementations18 Sep 2021 Hongruixuan Chen, Chen Wu, Yonghao Xu, Bo Du

To this end, a semantic-edge domain adaptation architecture is proposed, which uses an independent edge stream to process edge information, thereby generating high-quality semantic boundaries over the target domain.

Ranked #34 on Synthetic-to-Real Translation on GTAV-to-Cityscapes Labels (using extra training data)

Self-Supervised Learning Semantic Segmentation +2

Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images

1 code implementation18 Aug 2021 Hongruixuan Chen, Chen Wu, Bo Du

With the goal of designing a quite deep architecture to obtain more precise CD results while simultaneously decreasing parameter numbers to improve efficiency, in this work, we present a very deep and efficient CD network, entitled EffCDNet.

Change Detection

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 +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

Deep Siamese Domain Adaptation Convolutional Neural Network for Cross-domain Change Detection in Multispectral Images

no code implementations13 Apr 2020 Hongruixuan Chen, Chen Wu, Bo Du, Liangepei Zhang

In this paper, we propose a novel deep siamese domain adaptation convolutional neural network (DSDANet) architecture for cross-domain change detection.

Change Detection Domain Adaptation

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 Clustering +1

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

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