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Real-Time Semantic Image Segmentation with Deep Learning for Autonomous Driving: A Survey
| Content Provider | MDPI |
|---|---|
| Author | Papadeas, Ilias Tsochatzidis, Lazaros Amanatiadis, Angelos Pratikakis, Ioannis |
| Copyright Year | 2021 |
| Description | Semantic image segmentation for autonomous driving is a challenging task due to its requirement for both effectiveness and efficiency. Recent developments in deep learning have demonstrated important performance boosting in terms of accuracy. In this paper, we present a comprehensive overview of the state-of-the-art semantic image segmentation methods using deep-learning techniques aiming to operate in real time so that can efficiently support an autonomous driving scenario. To this end, the presented overview puts a particular emphasis on the presentation of all those approaches which permit inference time reduction, while an analysis of the existing methods is addressed by taking into account their end-to-end functionality, as well as a comparative study that relies upon a consistent evaluation framework. Finally, a fruitful discussion is presented that provides key insights for the current trend and future research directions in real-time semantic image segmentation with deep learning for autonomous driving. |
| Starting Page | 8802 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app11198802 |
| Journal | Applied Sciences |
| Issue Number | 19 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-09-22 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Transportation Science and Technology Semantic Image Segmentation Real Time Deep Learning Autonomous Driving |
| Content Type | Text |
| Resource Type | Article |
