Edge Intelligence Empowered Vehicle Detection and Image Segmentation for Autonomous Vehicles

Chen, Chen; Wang, Chenyu; Wang, Chenyu; He, Changchun; Li, Cong; Wan, Shaohua

doi:10.1109/tits.2022.3232153

Cited by 88 publications

(35 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 1 shows a comparison of the technical paths of SVI and VIC. The intelligent connected market industry's external ecological construction is based on information and communication technology behemoths, like Baidu, Tencent, Ali, and others, which have extensive user ecological coverage, as well as cutting-edge technologies, like artificial intelligence and big data [11]. As technology platform providers, these businesses engage closely with companies in the traditional automotive industry chain on vehicle networking, autonomous driving solutions, high-precision positioning, and other areas to help speed the industrialization of ICVs.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Game and Simulation Analysis of Intelligent Connected Vehicle Industry With Cross-Border Collaborative Innovation

Tang

Zhao

et al. 2023

IEEE Access

View full text Add to dashboard Cite

The Made in China 2025 national strategy has prioritized intelligent connected vehicles (ICV) to realize the intelligence and connection transformation and upgrading of the automotive industry, ushering in unprecedented development opportunities. There are two technology paths in the ICV industry: singlevehicle intelligence and vehicle-infrastructure collaboration. Both face problem of low technological innovation efficiency, and key to solving it is breaking down barriers between enterprises and realizing crossborder collaborative innovation. This study offers a new cross-border collaborative innovation development paradigm for the ICV industry, centered on automotive enterprises and technology platform providers. This study examines the impact of changes in key parameters on the evolutionary results using the system dynamics method to analyze the efficiency of cross-border collaborative innovation in the ICV industry. The simulation results showed that cross-border collaborative innovation is inevitable for the ICV industry. Furthermore, compared to the single-vehicle intelligence scenario, the vehicle-infrastructure collaboration scenario shows faster convergence between automotive enterprises and technology platform providers. Finally, the choice of system collaborative innovation strategy is influenced by default cost and the collaborative innovation risk coefficient, whereas the cost-sharing coefficient and network connection fee only have an impact on the cross-border collaborative innovation system's rate of evolution in the ICV industry.

show abstract

Section: Introductionmentioning

confidence: 99%

Evolutionary Game and Simulation Analysis of Intelligent Connected Vehicle Industry With Cross-Border Collaborative Innovation

Tang

Zhao

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…With the rapid development of 5G/6G technologies, the Internet of Vehicles (IoV) is becoming an important part of intelligent transportation system. Driven by the IoV technologies, computing-intensive and latency-sensitive applications for vehicles such as assisted driving, vehicle detection and high definition online map are gradually appearing [1][2][3]. The service providers can provide vehicles with road information as well as entertainment content, such as high-definition maps, videos etc., through mobile networks [4,5].…”

Section: Introductionmentioning

confidence: 99%

Vehicle clustering based edge caching scheme in internet of vehicles

Yang,

Tan,

Xie

et al. 2023

IET Communications

View full text Add to dashboard Cite

With the development of mobile edge computing technology, edge caching provides a feasible solution for low‐latency and high‐reliability data forwarding in the Internet of Vehicles (IoV). Due to the limited number and storage capacity of the edge servers, and the limited communication range of a single vehicle, the delay and connection requirements are hard to be satisfied. A vehicle clustering based edge caching scheme is proposed in this paper, aiming at minimizing the content acquisition delay of the requesting vehicles (RVs) within the communication range of the edge servers. After getting the optimal vehicle association results, the minimization of content acquisition delay is transformed into a knapsack problem, which is then solved by a dynamic programming algorithm to obtain the optimal cache decisions. Simulation results show that the proposed scheme reduces task acquisition delay by at least about 100 s and increases the cache hit rate by about 50%, compared with the random cache scheme.

show abstract

“…Machine learning [ 1 ], big data [ 2 , 3 ], and the Internet of Things (IoT) [ 4 ] have infiltrated every aspect of people's lives. Generative adversarial networks (GANs) [ 5 ] have been viewed as the most interesting ideas of artificial intelligence in the last decade.…”

Section: Introductionmentioning

confidence: 99%

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Zhang

Wang

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

Accurate semantic editing of the generated images is extremely important for machine learning and sample enhancement of big data. Aiming at the problem of semantic entanglement in generated image latent space of the StyleGAN2 network, we proposed a generated image editing method based on global-local Jacobi disentanglement. In terms of global disentanglement, we extract the weight matrix of the style layer in the pre-trained StyleGAN2 network; obtain the semantic attribute direction vector by using the weight matrix eigen decomposition method; finally, utilize this direction vector as the initialization vector for the Jacobi orthogonal regularization search algorithm. Our method improves the speed of the Jacobi orthogonal regularization search algorithm with the proportion of effective semantic attribute editing directions. In terms of local disentanglement, we design a local contrast regularized loss function to relax the semantic association local area and non-local area and utilize the Jacobi orthogonal regularization search algorithm to obtain a more accurate semantic attribute editing direction based on the local area prior MASK. The experimental results show that the proposed method achieves SOTA in semantic attribute disentangled metrics and can discover more accurate editing directions compared with the mainstream unsupervised generated image editing methods.

show abstract

Edge Intelligence Empowered Vehicle Detection and Image Segmentation for Autonomous Vehicles

Cited by 88 publications

References 34 publications

Evolutionary Game and Simulation Analysis of Intelligent Connected Vehicle Industry With Cross-Border Collaborative Innovation

Evolutionary Game and Simulation Analysis of Intelligent Connected Vehicle Industry With Cross-Border Collaborative Innovation

Vehicle clustering based edge caching scheme in internet of vehicles

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Contact Info

Product

Resources

About