Search Results for author: Jing Yao

Found 18 papers, 8 papers with code

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.

AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images

no code implementations14 Jan 2022 Kai-Ni Wang, Xin Yang, Juzheng Miao, Lei LI, Jing Yao, Ping Zhou, Wufeng Xue, Guang-Quan Zhou, Xiahai Zhuang, Dong Ni

Extensive experimental results on a publicly available dataset from Myocardial pathology segmentation combining multi-sequence CMR (MyoPS 2020) demonstrate our method can achieve promising performance compared with other state-of-the-art methods.

Learning to Select Historical News Articles for Interaction based Neural News Recommendation

no code implementations13 Oct 2021 Peitian Zhang, Zhicheng Dou, Jing Yao

The key to personalized news recommendation is to match the user's interests with the candidate news precisely and efficiently.

News Recommendation

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

Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model

1 code implementation21 May 2021 Danfeng Hong, Jingliang Hu, Jing Yao, Jocelyn Chanussot, Xiao Xiang Zhu

Moreover, to better assess multimodal baselines and the newly-proposed S2FL model, three multimodal RS benchmark datasets, i. e., Houston2013 -- hyperspectral and multispectral data, Berlin -- hyperspectral and synthetic aperture radar (SAR) data, Augsburg -- hyperspectral, SAR, and digital surface model (DSM) data, are released and used for land cover classification.

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).

PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field

no code implementations13 Sep 2020 Haixia Bi, Jing Yao, Zhiqiang Wei, Danfeng Hong, Jocelyn Chanussot

Polarimetric synthetic aperture radar (PolSAR) image classification has been investigated vigorously in various remote sensing applications.

Classification Data Augmentation +2

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

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.

Spatial-Spectral Manifold Embedding of Hyperspectral Data

no code implementations17 Jul 2020 Danfeng Hong, Jing Yao, Xin Wu, Jocelyn Chanussot, Xiao Xiang Zhu

In recent years, hyperspectral imaging, also known as imaging spectroscopy, has been paid an increasing interest in geoscience and remote sensing community.

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