DeepReflecs: Deep Learning for Automotive Object Classification with Radar Reflections

10/19/2020
by   Michael Ulrich, et al.
0

This paper presents an novel object type classification method for automotive applications which uses deep learning with radar reflections. The method provides object class information such as pedestrian, cyclist, car, or non-obstacle. The method is both powerful and efficient, by using a light-weight deep learning approach on reflection level radar data. It fills the gap between low-performant methods of handcrafted features and high-performant methods with convolutional neural networks. The proposed network exploits the specific characteristics of radar reflection data: It handles unordered lists of arbitrary length as input and it combines both extraction of local and global features. In experiments with real data the proposed network outperforms existing methods of handcrafted or learned features. An ablation study analyzes the impact of the proposed global context layer.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/25/2020

CNN based Road User Detection using the 3D Radar Cube

This letter presents a novel radar based, single-frame, multi-class dete...
research
02/17/2022

DeepHybrid: Deep Learning on Automotive Radar Spectra and Reflections for Object Classification

Automated vehicles need to detect and classify objects and traffic parti...
research
03/06/2023

Histogram-based Deep Learning for Automotive Radar

There are various automotive applications that rely on correctly interpr...
research
08/05/2021

3DRIMR: 3D Reconstruction and Imaging via mmWave Radar based on Deep Learning

mmWave radar has been shown as an effective sensing technique in low vis...
research
04/27/2023

TempEE: Temporal-Spatial Parallel Transformer for Radar Echo Extrapolation Beyond Auto-Regression

The meteorological radar reflectivity data, also known as echo, plays a ...
research
02/04/2019

Object Detection and 3D Estimation via an FMCW Radar Using a Fully Convolutional Network

This paper considers object detection and 3D estimation using an FMCW ra...
research
09/30/2020

One Reflection Suffice

Orthogonal weight matrices are used in many areas of deep learning. Much...

Please sign up or login with your details

Forgot password? Click here to reset