1.4k citations · 2k across the 17 of their papers we have counts for
29 papers
OpenEarthMap: A Benchmark Dataset for Global High-Resolution Land Cover Mapping
Junshi Xia, Naoto Yokoya, Bruno Adriano +1
We introduce OpenEarthMap, a benchmark dataset, for global high-resolution land cover mapping. OpenEarthMap consists of 2.2 million segments of 5000 aerial and satellite images cov…
EOD: The IEEE GRSS Earth Observation Database
Michael Schmitt, Pedram Ghamisi, Naoto Yokoya +1
In the era of deep learning, annotated datasets have become a crucial asset to the remote sensing community. In the last decade, a plethora of different datasets was published, eac…
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion
Danfeng Hong, Jing Yao, Deyu Meng +2
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perf…
ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Framework
Ningkai Mo, Wanshui Gan, Naoto Yokoya +1
In this paper, a computation efficient regression framework is presented for estimating the 6D pose of rigid objects from a single RGB-D image, which is applicable to handling symm…
Building Damage Mapping with Self-PositiveUnlabeled Learning
Junshi Xia, Naoto Yokoya, Bruno Adriano
Humanitarian organizations must have fast and reliable data to respond to disasters. Deep learning approaches are difficult to implement in real-world disasters because it might be…
Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
Danfeng Hong, Lianru Gao, Jing Yao +4
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 simultaneous…