912 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nanjing UniversityCN78 papers
- Centre National de la Recherche ScientifiqueFR49 papers
- Pennsylvania State UniversityUS48 papers
- Xi'an Jiaotong UniversityCN43 papers
- Center for Astrophysics Harvard & SmithsonianUS41 papers
- National Laboratory of Solid State Microstructures39 papers
- Argonne National LaboratoryUS38 papers
- Goddard Space Flight CenterUS38 papers
- Johns Hopkins UniversityUS31 papers
- Collaborative Innovation Center of Advanced MicrostructuresCN29 papers
- Université Paris-SaclayFR28 papers
- Tel Aviv UniversityIL26 papers
5 papers · 2 filters
Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping
Zhenfeng Shao, Gui Cheng, Deren Li +3
In a complex urban scene, observation from a single sensor unavoidably leads to voids in observations, failing to describe urban objects in a comprehensive manner. In this paper, w…
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
Thanh-Dat Truong, Chi Nhan Duong, Ngan Le +3
Semantic segmentation aims to predict pixel-level labels. It has become a popular task in various computer vision applications. While fully supervised segmentation methods have ach…
Pan-sharpening via High-pass Modification Convolutional Neural Network
Jiaming Wang, Zhenfeng Shao, Xiao Huang +3
Most existing deep learning-based pan-sharpening methods have several widely recognized issues, such as spectral distortion and insufficient spatial texture enhancement, we propose…
Error Propagation in Satellite Multi-image Geometry
Joseph L Mundy, Hank Theiss
This paper describes an investigation of the source of geospatial error in digital surface models (DSMs) constructed from multiple satellite images. In this study the uncertainty i…
Self-Supervised Learning via multi-Transformation Classification for Action Recognition
Duc Quang Vu, Ngan T. H. Le, Jia-Ching Wang
Self-supervised tasks have been utilized to build useful representations that can be used in downstream tasks when the annotation is unavailable. In this paper, we introduce a self…