Search Results for author: Bing Zhang

Found 33 papers, 13 papers with code

Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection

no code implementations23 Feb 2024 Chenyu Li, Bing Zhang, Danfeng Hong, Jing Yao, Jocelyn Chanussot

These factors also limit the performance of the well-known low-rank representation (LRR) models in terms of robustness on the separation of background and target features and the reliance on manual parameter selection.

Anomaly Detection

SpectralGPT: Spectral Remote Sensing Foundation Model

no code implementations13 Nov 2023 Danfeng Hong, Bing Zhang, Xuyang Li, YuXuan Li, Chenyu Li, Jing Yao, Naoto Yokoya, Hao Li, Pedram Ghamisi, Xiuping Jia, Antonio Plaza, Paolo Gamba, Jon Atli Benediktsson, Jocelyn Chanussot

The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner.

Change Detection Representation Learning +3

Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks

no code implementations26 Sep 2023 Danfeng Hong, Bing Zhang, Hao Li, YuXuan Li, Jing Yao, Chenyu Li, Martin Werner, Jocelyn Chanussot, Alexander Zipf, Xiao Xiang Zhu

Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on individual urban environments (e. g., single cities or regions).

Domain Adaptation Segmentation +1

Demystifying the Performance of Data Transfers in High-Performance Research Networks

no code implementations20 Aug 2023 Ehsan Saeedizade, Bing Zhang, Engin Arslan

High-speed research networks are built to meet the ever-increasing needs of data-intensive distributed workflows.

Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review

no code implementations13 May 2022 Minghua Wang, Danfeng Hong, Zhu Han, Jiaxin Li, Jing Yao, Lianru Gao, Bing Zhang, Jocelyn Chanussot

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of the Earth's surface at a distance of data acquisition devices, such as aircraft, spacecraft, and satellite.

Anomaly Detection Super-Resolution +1

Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review

no code implementations3 May 2022 Jiaxin Li, Danfeng Hong, Lianru Gao, Jing Yao, Ke Zheng, Bing Zhang, Jocelyn Chanussot

With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily available nowadays, which renders researchers an opportunity to tackle current geoscience applications in a fresh way.

Experimental quantum adversarial learning with programmable superconducting qubits

no code implementations4 Apr 2022 Wenhui Ren, Weikang Li, Shibo Xu, Ke Wang, Wenjie Jiang, Feitong Jin, Xuhao Zhu, Jiachen Chen, Zixuan Song, Pengfei Zhang, Hang Dong, Xu Zhang, Jinfeng Deng, Yu Gao, Chuanyu Zhang, Yaozu Wu, Bing Zhang, Qiujiang Guo, Hekang Li, Zhen Wang, Jacob Biamonte, Chao Song, Dong-Ling Deng, H. Wang

Our results reveal experimentally a crucial vulnerability aspect of quantum learning systems under adversarial scenarios and demonstrate an effective defense strategy against adversarial attacks, which provide a valuable guide for quantum artificial intelligence applications with both near-term and future quantum devices.

BIG-bench Machine Learning Quantum Machine Learning

SimPO: Simultaneous Prediction and Optimization

no code implementations31 Mar 2022 Bing Zhang, Yuya Jeremy Ong, Taiga Nakamura

Concretely, predictive models are often employed in estimating the parameters for the input values that are utilized for optimization models as isolated processes.

Decision Making

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

2 code implementations7 Jul 2021 Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot

Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies.

Classification Hyperspectral Image Classification

Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing

1 code implementation21 May 2021 Danfeng Hong, Lianru Gao, Jing Yao, Naoto Yokoya, Jocelyn Chanussot, Uta Heiden, Bing Zhang

Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneously generalize various spectral variabilities and extract physically meaningful endmembers still remains limited due to the poor ability in data fitting and reconstruction and the sensitivity to various spectral variabilities.

Hyperspectral Unmixing

Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain Adaptation

1 code implementation17 May 2021 Kelei He, Wen Ji, Tao Zhou, Zhuoyuan Li, Jing Huo, Xin Zhang, Yang Gao, Dinggang Shen, Bing Zhang, Junfeng Zhang

Specifically, a bidirectional image synthesis and segmentation module is proposed to segment the brain tumor using the intermediate data distributions generated for the two domains, which includes an image-to-image translator and a shared-weighted segmentation network.

Brain Tumor Segmentation Image Generation +3

Using Low-rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing

no code implementations30 Mar 2021 Lianru Gao, Zhicheng Wang, Lina Zhuang, Haoyang Yu, Bing Zhang, Jocelyn Chanussot

Tensor-based methods have been widely studied to attack inverse problems in hyperspectral imaging since a hyperspectral image (HSI) cube can be naturally represented as a third-order tensor, which can perfectly retain the spatial information in the image.

Hyperspectral Image Denoising and Anomaly Detection Based on Low-rank and Sparse Representations

1 code implementation12 Mar 2021 Lina Zhuang, Lianru Gao, Bing Zhang, Xiyou Fu, Jose M. Bioucas-Dias

Hyperspectral imaging measures the amount of electromagnetic energy across the instantaneous field of view at a very high resolution in hundreds or thousands of spectral channels.

Anomaly Detection Hyperspectral Image Denoising +1

Dissecting Energy Budget of a Gamma-Ray Burst Fireball

no code implementations9 Feb 2021 Bing Zhang, Yu Wang, Liang Li

The jet composition and radiative efficiency of GRBs are poorly constrained from the data.

High Energy Astrophysical Phenomena

Deep Encoder-Decoder Networks for Classification of Hyperspectral and LiDAR Data

1 code implementation IEEE Geoscience and Remote Sensing Letters 2020 Danfeng Hong, Lianru Gao, Renlong Hang, Bing Zhang, Jocelyn Chanussot

To overcome this limitation, we present a simple but effective multimodal DL baseline by following a deep encoder–decoder network architecture, EndNet for short, for the classification of hyperspectral and light detection and ranging (LiDAR) data.

Classification

More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1 code implementation12 Aug 2020 Danfeng Hong, Lianru Gao, Naoto Yokoya, Jing Yao, Jocelyn Chanussot, Qian Du, Bing Zhang

In particular, we also investigate a special case of multi-modality learning (MML) -- cross-modality learning (CML) that exists widely in RS image classification applications.

Classification General Classification +2

Graph Convolutional Networks for Hyperspectral Image Classification

1 code implementation6 Aug 2020 Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot

Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification, owing to their ability to capture spatial-spectral feature representations.

Classification General Classification +1

Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super-Resolution

1 code implementation28 Jul 2020 Ke Zheng, Lianru Gao, Wenzhi Liao, Danfeng Hong, Bing Zhang, Ximin Cui, Jocelyn Chanussot

In this work, an unsupervised deep learning-based fusion method - HyCoNet - that can solve the problems in HSI-MSI fusion without the prior PSF and SRF information is proposed.

Super-Resolution

Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning

1 code implementation28 Jul 2020 Lianru Gao, Danfeng Hong, Jing Yao, Bing Zhang, Paolo Gamba, Jocelyn Chanussot

However, the ability in the fusion of HS and MS images remains to be improved, particularly in large-scale scenes, due to the limited acquisition of HS images.

HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation

no code implementations21 May 2020 Kelei He, Chunfeng Lian, Bing Zhang, Xin Zhang, Xiaohuan Cao, Dong Nie, Yang Gao, Junfeng Zhang, Dinggang Shen

In this paper, we tackle the challenging task of prostate segmentation in CT images by a two-stage network with 1) the first stage to fast localize, and 2) the second stage to accurately segment the prostate.

Multi-Task Learning Segmentation

MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling

no code implementations15 May 2020 Kelei He, Chunfeng Lian, Ehsan Adeli, Jing Huo, Yang Gao, Bing Zhang, Junfeng Zhang, Dinggang Shen

Therefore, the proposed network has a dual-branch architecture that tackles two tasks: 1) a segmentation sub-network aiming to generate the prostate segmentation, and 2) a voxel-metric learning sub-network aiming to improve the quality of the learned feature space supervised by a metric loss.

Metric Learning Multi-Task Learning +2

On the FRB luminosity function -- II. Event rate density

1 code implementation10 Mar 2020 Rui Luo, Yunpeng Men, Kejia Lee, Weiyang Wang, D. R. Lorimer, Bing Zhang

Assuming a Schechter luminosity function form, we infer (at the 95% confidence level) that the characteristic FRB event rate density at the upper cut-off luminosity $L^*=2. 9_{-1. 7}^{+11. 9}\times10^{44}\,\rm erg\, s^{-1}$ is $\phi^*=339_{-313}^{+1074}\,\rm Gpc^{-3}\, yr^{-1}$, the power-law index is $\alpha=-1. 79_{-0. 35}^{+0. 31}$, and the lower cut-off luminosity is $L_0\le9. 1\times10^{41}\,\rm erg\, s^{-1}$.

High Energy Astrophysical Phenomena Cosmology and Nongalactic Astrophysics

A Fast and Precise Method for Large-Scale Land-Use Mapping Based on Deep Learning

no code implementations9 Aug 2019 Xuan Yang, Zhengchao Chen, Baipeng Li, Dailiang Peng, Pan Chen, Bing Zhang

The land-use map is an important data that can reflect the use and transformation of human land, and can provide valuable reference for land-use planning.

Classification General Classification +1

Second Repeating FRB 180814.J0422+73: Ten-year Fermi-LAT Upper limits and Implications

no code implementations18 Mar 2019 Yu-Han Yang, Bin-Bin Zhang, Bing Zhang

The second repeating fast radio burst source, FRB 180814. J0422+73, was detected recently by the CHIME collaboration.

High Energy Astrophysical Phenomena

Investigation of the asteroid-neutron star collision model for the repeating fast radio bursts

no code implementations14 Feb 2019 Jeremy L. Smallwood, Rebecca G. Martin, Bing Zhang

The origin of fast radio bursts (FRBs) is still a mystery.

High Energy Astrophysical Phenomena Earth and Planetary Astrophysics

A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions

no code implementations5 Dec 2018 Kai Lei, Bing Zhang, Yong liu, Yang Deng, Dongyu Zhang, Ying Shen

In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.

Entity Linking Learning-To-Rank +5

On the normalised FRB luminosity function

2 code implementations29 Aug 2018 Rui Luo, Kejia Lee, Duncan R. Lorimer, Bing Zhang

In this paper, we measure the normalised luminosity function of FRBs.

High Energy Astrophysical Phenomena

Learning to score the figure skating sports videos

1 code implementation8 Feb 2018 Chengming Xu, Yanwei Fu, Bing Zhang, Zitian Chen, Yu-Gang Jiang, xiangyang xue

This paper targets at learning to score the figure skating sports videos.

Cannot find the paper you are looking for? You can Submit a new open access paper.