Search Results for author: Cheng Hu

Found 7 papers, 0 papers with code

Attention and Prediction Guided Motion Detection for Low-Contrast Small Moving Targets

no code implementations27 Apr 2021 Hongxin Wang, Jiannan Zhao, Huatian Wang, Cheng Hu, Jigen Peng, Shigang Yue

The developed visual system comprises three main subsystems, namely, an attention module, an STMD-based neural network, and a prediction module.

Motion Detection

A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments

no code implementations29 Dec 2019 Hongxin Wang, Huatian Wang, Jiannan Zhao, Cheng Hu, Jigen Peng, Shigang Yue

Discriminating small moving objects within complex visual environments is a significant challenge for autonomous micro robots that are generally limited in computational power.

Motion Detection

Synthetic Neural Vision System Design for Motion Pattern Recognition in Dynamic Robot Scenes

no code implementations15 Apr 2019 Qinbing Fu, Cheng Hu, Pengcheng Liu, Shigang Yue

The presented system is a synthetic neural network, which comprises two complementary sub-systems with four spiking neurons -- the lobula giant movement detectors (LGMD1 and LGMD2) in locusts for sensing looming and recession, and the direction selective neurons (DSN-R and DSN-L) in flies for translational motion extraction.

Decision Making

An LGMD Based Competitive Collision Avoidance Strategy for UAV

no code implementations15 Apr 2019 Jiannan Zhao, Xingzao Ma, Qinbing Fu, Cheng Hu, Shigang Yue

In this paper, we present an LGMD based competitive collision avoidance method for UAV indoor navigation.

A Bio-inspired Collision Detecotr for Small Quadcopter

no code implementations14 Jan 2018 Jiannan Zhao, Cheng Hu, Chun Zhang, Zhihua Wang, Shigang Yue

The observed results from the experiments demonstrated that the LGMD collision detector is feasible to work as a vision module for the quadcopter's collision avoidance task.

Collision Selective Visual Neural Network Inspired by LGMD2 Neurons in Juvenile Locusts

no code implementations22 Dec 2017 Qinbing Fu, Cheng Hu, Shigang Yue

The results demonstrated this framework is able to detect looming dark objects embedded in bright backgrounds selectively, which make it ideal for ground mobile platforms.

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