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Review on Millimeter-Wave Radar and Camera Fusion Technology
2022
Sustainability
Preserved Fulltext
The data fusion algorithms from MMW radar and camera are described separately from traditional fusion algorithms and deep learning based algorithms, and their advantages and disadvantages are briefly evaluated ...
MMW radar and camera, as two sensors with complementary strengths, have been heavily researched in intelligent transportation. ...
Lim [122] proposed a new deep learning architecture fusing radar signals and camera images, in which the radar and camera branches are tested, trained, and extracted separately. ...
doi:10.3390/su14095114
fatcat:xozsw2auhjbpbccyf3flsfnvje
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
[article]
2020
arXiv
pre-print
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Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task ...
Almost at the same time, deep learning has made breakthrough by several pioneers, three of them (also called fathers of deep learning), Hinton, Bengio and LeCun, won ACM Turin Award in 2019. ...
of two detections exploits both appearance and motion via a Siamese network. ...
arXiv:2006.06091v3
fatcat:nhdgivmtrzcarp463xzqvnxlwq
Papers by Title
2021
2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)
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Estimation of Road Structures via Attention Branch Network with Text Data Degradation of Metal Corner Reflectors' Radar Cross-Section in a Radome with Imperfect Characteristics Delay-based Task Offloading ...
Method with Combined Loss of Triplet Network and Autoencoder A Development Support Tool for Fault-tolerant Routing Methods on Network-on-Chips A DRL based Real-time Computing Load Scheduling Method A ...
doi:10.1109/icce-tw52618.2021.9602951
fatcat:x5phgfzzl5cafcxul53thv5w7e
Development and Experimental Validation of High Performance Embedded Intelligence and Fail-Operational Urban Surround Perception Solutions of the PRYSTINE Project
2021
Applied Sciences
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If a fault is detected via a monitoring component, a restart of the platform recovers the system. ...
The sensor data are sent to the controllers via diverse communication channels, thus mitigating systematic faults. ...
doi:10.3390/app12010168
fatcat:t5gwp45w4rg33djn2upzatzyii
Providentia – A Large-Scale Sensor System for the Assistance of Autonomous Vehicles and Its Evaluation
2022
Field Robotics
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However, these errors could be reduced by retraining our detection network with an additional van class, such that it learns to better differentiate. ...
Not only are the multiple camera streams processed in parallel; the object detection can also work with various detection networks. ...
doi:10.55417/fr.2022038
fatcat:evxuyka32vatxpadvcb7lebngm
Providentia – A Large-Scale Sensor System for the Assistance of Autonomous Vehicles and Its Evaluation
[article]
2021
arXiv
pre-print
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However, these errors could be reduced by retraining our detection network with an additional van class, such that it learns to better differentiate. ...
Not only are the multiple camera streams processed in parallel, the object detection can also work with various detection networks. ...
arXiv:1906.06789v5
fatcat:44jektp4fjgzhgpccrtznhkzbm
2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Dey, S., +, JSTARS 2021 8744-8760 Synthetic Aperture Radar Image Change Detection via Siamese Adaptive Fusion Network. ...
., +, JSTARS 2021 9475-9485 SANet: A Sea-Land Segmentation Network Via Adaptive Multiscale Feature Learning. ...
., Hyperspectral Image Superresolution via Deep Structure and Texture Interfusion; JSTARS 2021 8665-8678 Hu, J., see Feng, D., JSTARS 2021 12212-12223 Hu, J., Shen, X., Yu, H., Shang, X., Guo, Q., ...
doi:10.1109/jstars.2022.3143012
fatcat:dnetkulbyvdyne7zxlblmek2qy
D2.1 State-of-the-art methods in Digital Twinning for motion-driven high-tech applications
2023
Zenodo
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Event camera
Partner solutions (any TRL)
3.3.4.1 Radar IMST starts with the "RoKoRa" radar (a result of a funded research project), which is a 77 GHz radar module with 3 Tx and 4 Rx channels with integrated ...
Overcoming the gap between simulation and reality and successfully transferring perception and action learned in simulators to real robots in real environments (Sim2Real) is a newer branch of AI, combining ...
doi:10.5281/zenodo.7597970
fatcat:dvhqqnznefgjjasfoct3jxfp4m
D2.1 State-of-the-art methods in Digital Twinning for motion-driven high-tech applications
2022
Zenodo
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Event camera
Partner solutions (any TRL)
3.3.4.1 Radar IMST starts with the "RoKoRa" radar (a result of a funded research project), which is a 77 GHz radar module with 3 Tx and 4 Rx channels with integrated ...
Overcoming the gap between simulation and reality and successfully transferring perception and action learned in simulators to real robots in real environments (Sim2Real) is a newer branch of AI, combining ...
doi:10.5281/zenodo.7575975
fatcat:mzrn3ma6zfep7clihcqsrhwuxe
Contact and Remote Breathing Rate Monitoring Techniques: A Review
2021
IEEE Sensors Journal
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Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. ...
While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. ...
Normal and abnormal breathing patterns were classified from such video through a deep learning neural network. ...
doi:10.1109/jsen.2021.3072607
pmid:35789086
pmcid:PMC8769001
fatcat:gwmdr6stfrhdvjimjznfavexim
2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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., +, JSTARS 2020 5508-5517 Branch Feature Fusion Convolution Network for Remote Sensing Scene Classification. ...
., +, JSTARS 2020 5508-5517 Branch Feature Fusion Convolution Network for Remote Sensing Scene Classification. ...
A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020 ...
doi:10.1109/jstars.2021.3050695
fatcat:ycd5qt66xrgqfewcr6ygsqcl2y
2019 Index IEEE Transactions on Intelligent Transportation Systems Vol. 20
2019
IEEE transactions on intelligent transportation systems (Print)
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., +, TITS June
2019 2339-2352
Fault diagnosis
A Newly Robust Fault Detection and Diagnosis Method for High-Speed
Trains. ...
Murca, M.C.R., +, TITS May 2019 1683-1696 Learning to Predict Bus Arrival Time From Heterogeneous Measurements via Recurrent Neural Network. ...
doi:10.1109/tits.2020.2966388
fatcat:xkvww7uabzhlzgfz3yiecyb75y
Safety Assessment for Autonomous Systems' Perception Capabilities
[article]
2022
arXiv
pre-print
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The sensor processing typically makes use of Machine Learning (ML) and has to work in challenging environments, further the ML-algorithms have known limitations,e.g., the possibility of false-negatives ...
These subsystems are typically multi-modal, i.e. use multiple sensor types, and often employ Machine Learning (ML) for processing data from optical sensors, especially cameras. ...
In the main body of the paper we will treat:ACC and ALC via the HAZOP methodology further ALKS capabilities (AEB FCW LDW) will be treated in annexes: Appendix A. ...
arXiv:2208.08237v2
fatcat:jrj2uolu7nefndb4ypo7ykm5ca
2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70
2021
IEEE Transactions on Instrumentation and Measurement
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., +, TIM 2021 7000109 Machine Learning-Based Network Status Detection and Fault Localization. ...
Gao, F., +, TIM 2021 5016512 Visual Landmark Learning Via Attention-Based Deep Neural Networks. ...
doi:10.1109/tim.2022.3156705
fatcat:dmqderzenrcopoyipv3v4vh4ry
A survey of deep learning techniques for autonomous driving
2019
Journal of Field Robotics
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2019 pre-print arXiv:1910.07738v1 fatcat:5s5ldjkko5bs7mmb4ro3mallgeOther Versions
We start by presenting AI-based self-driving architectures, convolutional and recurrent neural networks, as well as the deep reinforcement learning paradigm. ...
The objective of this paper is to survey the current state-of-the-art on deep learning technologies used in autonomous driving. ...
For example, alongside three Lidar sensors, Waymo also makes use of five radars and eight cameras, while Tesla ® cars are equipped with eights cameras, 12 ultrasonic sensors and one forward-facing radar ...
doi:10.1002/rob.21918
fatcat:pjyk4lwjavf63jz4pmc3mnuqe4
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