1.7k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN81 papers
- University of Chinese Academy of SciencesCN44 papers
- Centre National de la Recherche ScientifiqueFR12 papers
- Institut polytechnique de GrenobleFR12 papers
- Université Grenoble AlpesFR12 papers
- GIPSA-LabFR8 papers
- Laboratoire Jean KuntzmannFR6 papers
- Xi'an Jiaotong UniversityCN6 papers
- Chongqing UniversityCN5 papers
- Institut national de recherche en sciences et technologies du numériqueFR5 papers
- International Research Center of Big Data for Sustainable Development GoalsCN5 papers
- Tsinghua UniversityCN5 papers
11 papers · 1 filter
Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification
Ying Qu, Razieh Kaviani Baghbaderani, Wei Li +2
Hyperspectral image (HSI) classification is one of the most active research topics and has achieved promising results boosted by the recent development of deep learning. However, m…
More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification
Danfeng Hong, Lianru Gao, Naoto Yokoya +4
Classification and identification of the materials lying over or beneath the Earth's surface have long been a fundamental but challenging research topic in geoscience and remote se…
Graph Convolutional Networks for Hyperspectral Image Classification
Danfeng Hong, Lianru Gao, Jing Yao +3
To read the final version please go to IEEE TGRS on IEEE Xplore. Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classifi…
Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super-Resolution
Ke Zheng, Lianru Gao, Wenzhi Liao +4
Due to the limitations of hyperspectral imaging systems, hyperspectral imagery (HSI) often suffers from poor spatial resolution, thus hampering many applications of the imagery. Hy…
Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning
Lianru Gao, Danfeng Hong, Jing Yao +3
Extensive attention has been widely paid to enhance the spatial resolution of hyperspectral (HS) images with the aid of multispectral (MS) images in remote sensing. However, the ab…
X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
Danfeng Hong, Naoto Yokoya, Gui-Song Xia +2
This paper addresses the problem of semi-supervised transfer learning with limited cross-modality data in remote sensing. A large amount of multi-modal earth observation images, su…
Taking the pulse of COVID-19: A spatiotemporal perspective
Chaowei Yang, Dexuan Sha, Qian Liu +32
The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including…
Study on the atmospheric pressure homogeneous discharge in air assisted with a floating carbon fibre microelectrode
Shuai Zhao, Yong Hao, Tao Qiao +1
Based on the consideration of increasing the number of initial electrons and providing an appropriate distribution of electric field strength for discharge space, a method of adopt…
A Biologically Interpretable Two-stage Deep Neural Network (BIT-DNN) For Vegetation Recognition From Hyperspectral Imagery
Yue Shi, Liangxiu Han, Wenjiang Huang +4
Spectral-spatial based deep learning models have recently proven to be effective in hyperspectral image (HSI) classification for various earth monitoring applications such as land…
Object Relational Graph with Teacher-Recommended Learning for Video Captioning
Ziqi Zhang, Yaya Shi, Chunfeng Yuan +4
Taking full advantage of the information from both vision and language is critical for the video captioning task. Existing models lack adequate visual representation due to the neg…
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning
Zhongling Huang, Corneliu Octavian Dumitru, Zongxu Pan +2
The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with e…