Review the state-of-the-art technologies of semantic segmentation based on deep learning

Y Mo, Y Wu, X Yang, F Liu, Y Liao - Neurocomputing, 2022 - Elsevier
The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Perception and sensing for autonomous vehicles under adverse weather conditions: A survey

Y Zhang, A Carballo, H Yang, K Takeda - ISPRS Journal of …, 2023 - Elsevier
Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

Multi-class road user detection with 3+ 1d radar in the view-of-delft dataset

A Palffy, E Pool, S Baratam, JFP Kooij… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
Next-generation automotive radars provide elevation data in addition to range-, azimuth-and
Doppler velocity. In this experimental study, we apply a state-of-the-art object detector …

A survey on safety-critical driving scenario generation—a methodological perspective

W Ding, C Xu, M Arief, H Lin, B Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …

[HTML][HTML] Vehicle-to-everything (V2X) in the autonomous vehicles domain–A technical review of communication, sensor, and AI technologies for road user safety

SA Yusuf, A Khan, R Souissi - Transportation Research Interdisciplinary …, 2024 - Elsevier
Autonomous vehicles (AV) are rapidly becoming integrated into everyday life, with several
countries anticipating their inclusion in public transport networks in the coming years. Safety …

Scan context++: Structural place recognition robust to rotation and lateral variations in urban environments

G Kim, S Choi, A Kim - IEEE Transactions on Robotics, 2021 - ieeexplore.ieee.org
Place recognition is a key module in robotic navigation. The existing line of studies mostly
focuses on visual place recognition to recognize previously visited places solely based on …

Deep learning-based robust positioning for all-weather autonomous driving

Y Almalioglu, M Turan, N Trigoni… - Nature machine …, 2022 - nature.com
Interest in autonomous vehicles (AVs) is growing at a rapid pace due to increased
convenience, safety benefits and potential environmental gains. Although several leading …

Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges

D Feng, C Haase-Schütz, L Rosenbaum… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …

[HTML][HTML] Towards deep radar perception for autonomous driving: Datasets, methods, and challenges

Y Zhou, L Liu, H Zhao, M López-Benítez, L Yu, Y Yue - Sensors, 2022 - mdpi.com
With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

Millimeter wave fmcw radars for perception, recognition and localization in automotive applications: A survey

A Venon, Y Dupuis, P Vasseur… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
MmWave (millimeter wave) Frequency Modulated Continuous Waves (FMCW) RADARs are
sensors based on frequency-modulated electromagnetic which see their environment in 3D …