Search Results for author: Shengyang Li

Found 7 papers, 3 papers with code

Planetary UAV localization based on Multi-modal Registration with Pre-existing Digital Terrain Model

no code implementations24 Jun 2021 Xue Wan, Yuanbin Shao, Shengyang Li

In this paper, we proposed a multi-modal registration based SLAM algorithm, which estimates the location of a planet UAV using a nadir view camera on the UAV compared with pre-existing digital terrain model.

On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID

1 code implementation22 Jun 2020 Yang Long, Gui-Song Xia, Shengyang Li, Wen Yang, Michael Ying Yang, Xiao Xiang Zhu, Liangpei Zhang, Deren Li

After reviewing existing benchmark datasets in the research community of RS image interpretation, this article discusses the problem of how to efficiently prepare a suitable benchmark dataset for RS image interpretation.

General Classification Image Classification +1

CNNTOP: a CNN-based Trajectory Owner Prediction Method

no code implementations5 Jan 2020 Xucheng Luo, Shengyang Li, Yuxiang Peng

In this paper, we propose a novel CNN-based Trajectory Owner Prediction (CNNTOP) method.

Attribute Representation Learning

How Agile is the Adaptive Data Rate Mechanism of LoRaWAN?

1 code implementation28 Aug 2018 Shengyang Li, Usman Raza, Aftab Khan

The LoRaWAN based Low Power Wide Area networks aim to provide long-range connectivity to a large number of devices by exploiting limited radio resources.

Networking and Internet Architecture

Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models

no code implementations16 Jul 2018 Xin-Yi Tong, Gui-Song Xia, Qikai Lu, Huanfeng Shen, Shengyang Li, Shucheng You, Liangpei Zhang

The main idea is to rely on deep neural networks for presenting the contextual information contained in different types of land-covers and propose a pseudo-labeling and sample selection scheme for improving the transferability of deep models.

Classification Domain Adaptation +6

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