Sensing and Semantic Perception in Autonomous Driving
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (1 November 2022) | Viewed by 10128
Special Issue Editors
Interests: Semantic Perception; Autonomous Robots; Imitation Learning
Interests: Robot Learning; Scene Understanding; Navigation
Special Issue Information
Dear Colleagues,
Sensing is an essential requirement to understand the surroundings in autonomous systems. Semantic perception accelerates the process of contextual understanding of the surroundings by predicting a meaningful class label for each sensed data point. A fine-grained semantic perception of the sensed data stream can, to a great extent, help to reach full autonomy in safety-critical systems such as autonomous vehicles.
This Special Issue aims to capture the latest developments in sensing technologies and semantic perception algorithms in the field of autonomous driving. We are aiming to compare various state-of-the-art approaches for generic sensing and semantic perception methods both in computer vision and robotic communities. Furthermore, this Special Issue will gather information about advanced deep neural network models for semantic environment perception. We, therefore, call for submissions of novel solutions that target developing AI-based smart sensing methodologies and intelligent perception approaches.
Prof. Dr. Eren Erdal Aksoy
Prof. Dr. Abhinav Valada
Prof. Dr. Jean-Emmanuel Deschaud
Guest Editors
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Keywords
- Sensing methodologies
- Smart sensors
- Semantic perception
- Semantic segmentation
- Panoptic segmentation
- Object detection
- Deep learning
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