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Exploring Deep Spiking Neural Networks for Automated Driving Applications., , , , and . VISIGRAPP (5: VISAPP), page 548-555. SciTePress, (2019)Realistic Ultrasonic Environment Simulation Using Conditional Generative Adversarial Networks., , , and . IV, page 2278-2283. IEEE, (2019)Challenges in Designing Datasets and Validation for Autonomous Driving., , , and . VISIGRAPP (5: VISAPP), page 653-659. SciTePress, (2019)Real-Time Dynamic Object Detection for Autonomous Driving Using Prior 3D-Maps., , , , , , , , and . ECCV Workshops (5), volume 11133 of Lecture Notes in Computer Science, page 567-582. Springer, (2018)Design of Real-time Semantic Segmentation Decoder for Automated Driving., , , and . VISIGRAPP (5: VISAPP), page 393-400. SciTePress, (2019)FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Driving., , , , , , and . CoRR, (2019)Woodscape Fisheye Object Detection for Autonomous Driving - CVPR 2022 OmniCV Workshop Challenge., , , , and . CoRR, (2022)MODNet: Moving Object Detection Network with Motion and Appearance for Autonomous Driving., , , , , and . CoRR, (2017)Let's Get Dirty: GAN Based Data Augmentation for Soiling and Adverse Weather Classification in Autonomous Driving., , , , , , and . CoRR, (2019)Monocular three-dimensional object detection using data augmentation and self-supervised learning in autonomous driving., , , , , , and . J. Electronic Imaging, (2022)