Search Results for author: Junfeng Chen

Found 7 papers, 4 papers with code

Deep-OSG: Deep Learning of Operators in Semigroup

no code implementations7 Feb 2023 Junfeng Chen, Kailiang Wu

It is a sequel to the previous flow map learning (FML) works [T. Qin, K. Wu, and D. Xiu, J. Comput.

Abnormal Occupancy Grid Map Recognition using Attention Network

1 code implementation18 Oct 2021 Fuqin Deng, Hua Feng, Mingjian Liang, Qi Feng, Ningbo Yi, Yong Yang, Yuan Gao, Junfeng Chen, Tin Lun Lam

The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it.

AcousticFusion: Fusing Sound Source Localization to Visual SLAM in Dynamic Environments

no code implementations3 Aug 2021 Tianwei Zhang, Huayan Zhang, Xiaofei Li, Junfeng Chen, Tin Lun Lam, Sethu Vijayakumar

Dynamic objects in the environment, such as people and other agents, lead to challenges for existing simultaneous localization and mapping (SLAM) approaches.

Depth Estimation Object +1

A Two-stage Unsupervised Approach for Low light Image Enhancement

no code implementations19 Oct 2020 Junjie Hu, Xiyue Guo, Junfeng Chen, Guanqi Liang, Fuqin Deng, Tin Lun Lam

However, most of them suffer from the following problems: 1) the need of pairs of low light and normal light images for training, 2) the poor performance for dark images, 3) the amplification of noise.

Low-Light Image Enhancement Simultaneous Localization and Mapping +1

Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment

3 code implementations19 Oct 2020 Xiyue Guo, Junjie Hu, Junfeng Chen, Fuqin Deng, Tin Lun Lam

The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL).

Graph Matching Simultaneous Localization and Mapping

U-net architectures for fast prediction of incompressible laminar flows

3 code implementations25 Oct 2019 Junfeng Chen, Jonathan Viquerat, Elie Hachem

Machine learning is a popular tool that is being applied to many domains, from computer vision to natural language processing.

Computational Physics Image and Video Processing

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