In the 6th year of Emperor Qianlong's reign, the girl Wei Yingluo became a maid in the Forbidden City to seek the truth of her sister's death. After investigation, she found her sister's death was related to prince Hongzhou, and she determined to revenge for her sister. The Empress Fucha was very kind, who worried Ying Luo would take the wrong way and gave her warmth and help. With the help of the Empress, Wei Yingluo grew to be an honest and strong female official in the palace, and she let go of her resentment and lived her life seriously. Yet the Empress passed away unfortunately, which made Yingluo misunderstand Emperor Qianlong. They were hostile to each other at first, but then they understood and supported each other.

Story of Yanxi Palace (Chinese Edition)

周默

Jiuzhou Press

木鉴(中国古代家具用材鉴赏)(精)

Jiangsu Phoenix Fine Arts Publishing House

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 collaboration applications, it proposes a series of exploratory contents such as practical fusion datasets, vehicle-road collaboration, and fusion mechanisms. In contrast to the existing literature on data fusion and autonomous driving, this book focuses more on the deep fusion method for perception-related tasks, emphasizes the theoretical explanation of the fusion method, and fully considers the relevant scenarios in engineering practice. Helping readers acquire an in-depth understanding of fusion methods and theories in autonomous driving, it can be used as a textbook for graduate students and scholars in related fields or as a reference guide for engineers who wish to apply deep fusion methods.

Multi-sensor Fusion for Autonomous Driving

Computers & Technology

Li, Jun

王蠡

Liu, Huaping

Li, Zhiwei

Zhang, Xinyu

Zou, Zhenhong

Computer Science

Springer

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