An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks

An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks

Aimed at improving size, weight, and power (SWaP)-constrained robotic vision-aided state estimation, we describe our unsupervised, deep convolutional-deconvolutional sensor fusion network, Multi-Hypothesis DeepEfference (MHDE). MHDE learns to intelligently combine noisy heterogeneous sensor data to...

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Bibliographic Details
Main Authors:	E. Jared Shamwell, William D. Nothwang, Donald Perlis
Format:	Article
Language:	English
Published:	MDPI AG 2018-05-01
Series:	Sensors
Subjects:	deep learning sensor fusion optical flow
Online Access:	http://www.mdpi.com/1424-8220/18/5/1427

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