Deep Multimodal Detection in Reduced Visibility Using Thermal Depth Estimation for Autonomous Driving

Deep Multimodal Detection in Reduced Visibility Using Thermal Depth Estimation for Autonomous Driving

Recently, the rapid development of convolutional neural networks (CNN) has consistently improved object detection performance using CNN and has naturally been implemented in autonomous driving due to its operational potential in real-time. Detecting moving targets to realize autonomous driving is an...

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Bibliographic Details
Main Authors: Cho, J. (Author), Yoon, S. (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
autonomous driving
Autonomous driving
Autonomous vehicles
Condition
Convolutional neural network
Convolutional neural networks
Dehazing
Demulsification
depth estimation
Depth Estimation
Detection performance
image dehazing
Image dehazing
Image enhancement
Image fusion
Image reconstruction
Moving targets
object detection
Object detection
Object recognition
Objects detection
Restoration
Thermal images
Visibility
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