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Titlebook: Autonomous driving algorithms and Its IC Design; Jianfeng Ren,Dong Xia Book 2023 Publishing House of Electronics Industry 2023 Autonomous

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41#
發(fā)表于 2025-3-28 15:07:36 | 只看該作者
42#
發(fā)表于 2025-3-28 21:24:25 | 只看該作者
https://doi.org/10.1007/978-1-84882-981-7f self-driving cars. However, many problems make it impossible for SLAM algorithms to drive vehicles for hundreds of kilometers under very different conditions. There are two main problems dealing with SLAM for self-driving cars: (1) localization drifts over time and (2) maps may not necessarily sat
43#
發(fā)表于 2025-3-29 01:35:39 | 只看該作者
44#
發(fā)表于 2025-3-29 04:41:23 | 只看該作者
Positive Definite Completion Problem,ort the development of autonomous vehicles around this trend. This chapter focuses on reviewing how the industry is currently meeting the challenges of semiconductor technology innovation in this field.
45#
發(fā)表于 2025-3-29 10:52:16 | 只看該作者
Laplacian Eigenvalues of Threshold Graphs,nity and has made great strides in the past few years..This chapter divides these methods into four categories: (1) parameter pruning and sharing; (2) low-rank factorization; (3) transfer/compact convolutional filters; and (4) knowledge distillation. For parameter pruning- and sharing-based solution
46#
發(fā)表于 2025-3-29 11:43:17 | 只看該作者
https://doi.org/10.1007/978-1-84882-981-7n intervention, however, it requires a complex sensor framework that captures not only vehicle data but also data from its surroundings. These sensors include LiDAR, radar, video, cameras, and more, which continuously generate massive amounts of data about the environment around the car in real time
47#
發(fā)表于 2025-3-29 19:27:57 | 只看該作者
https://doi.org/10.1007/978-1-84882-981-7re in a CPU, DSP, or GPU, but these algorithms are expensive and may have other drawbacks. CPUs cannot be fast or efficient enough, while DSPs are good at image processing but lack sufficient performance for deep AI. While GPUs are good at training, they are too power hungry. Another option for in-v
48#
發(fā)表于 2025-3-29 21:34:03 | 只看該作者
Laplacian Eigenvalues of Threshold Graphs,ngineering, and the architectures used to build autonomous driving systems. The development of autonomous driving systems involves domain-specific algorithms, architectures, systems engineering, and technical measures. In this chapter, we mainly introduce some open source operating systems and comme
49#
發(fā)表于 2025-3-29 23:55:47 | 只看該作者
Laplacian Eigenvalues of Threshold Graphs,t of information from the cars, making the right decisions, and building the software algorithms. This processing requires massive software implementation. There is one trend, both in industry and academia, to consolidate clusters of more powerful application processors and accelerators into higher-
50#
發(fā)表于 2025-3-30 07:28:47 | 只看該作者
Connectedness, Trees, and Hypergraphs,ability and economies of scale. In June 2017, 3GPP introduced cellular vehicle-to-everything (C-V2X) technology in Release 14 of its standard, and the technology was further developed with Release 15, which was completed in June 2019. This cellular technology is made possible by leveraging LTE and 5
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