| 书目名称 | Multi-sensor Fusion for Autonomous Driving | | 编辑 | Xinyu Zhang,Jun Li,Zhenhong Zou | | 视频video | | | 概述 | The first comprehensive and systematic introduction to multi-sensor fusion for autonomous driving.Addresses the theory of deep multi-sensor fusion from the perspective of uncertainty for both models a | | 图书封面 |  | | 描述 | .Although sensor fusion is an essential prerequisite for autonomous driving, it entails a number of challenges and potential risks. For example, the commonly used deep fusion networks are lacking in interpretability and robustness. To address these fundamental issues, this book introduces the mechanism of deep fusion models from the perspective of uncertainty and models the initial risks in order to create a robust fusion architecture...This book reviews the multi-sensor data fusion methods applied in autonomous driving, and the main body is divided into three parts: Basic, Method, and Advance. Starting from the mechanism of data fusion, it comprehensively reviews the development of automatic perception technology and data fusion technology, and gives a comprehensive overview of various perception tasks based on multimodal data fusion. The book then proposes a series of innovative algorithms for various autonomous driving perception tasks, to effectively improve the accuracy and robustness of autonomous driving-related tasks, and provide ideas for solving the challenges in multi-sensor fusion methods. Furthermore, to transition from technical research to intelligent connected colla | | 出版日期 | Book 2023 | | 关键词 | Autonomous driving; robotics; computer vision; multimodal perception; data fusion; sensor management; unce | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-3280-1 | | isbn_softcover | 978-981-99-3282-5 | | isbn_ebook | 978-981-99-3280-1 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 17:02:17
