Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Chen Junzhou"'
Publikováno v:
Journal of Aeronautical Materials, Vol 44, Iss 2, Pp 60-71 (2024)
Ultra-high strength aluminum alloy has achieved extensive application in the nuclear，aerospace，and aviation industries because of its high specific strength and low density. The fifth generation of ultra-high strength aluminum alloy has been prod
Externí odkaz:
https://doaj.org/article/19fdd8b5c5b5412184085b439d38f08f
Publikováno v:
Materials & Design, Vol 230, Iss , Pp 111979- (2023)
Gradient nanostructured materials are regarded as a promising class of architectures with tunable mechanical properties, primarily dependent on the optimization of well-controlled fabrication parameters. In this paper, a microvariable-based constitut
Externí odkaz:
https://doaj.org/article/bdb6b2021d374952b8a214789166a00b
Autor:
Chen, Junzhou, Huang, Heqiang, Zhang, Ronghui, Lyu, Nengchao, Guo, Yanyong, Dai, Hong-Ning, Yan, Hong
Ensuring safety in both autonomous driving and advanced driver-assistance systems (ADAS) depends critically on the efficient deployment of traffic sign recognition technology. While current methods show effectiveness, they often compromise between sp
Externí odkaz:
http://arxiv.org/abs/2410.17144
Autor:
Zhang, Ronghui, Yang, Shangyu, Lyu, Dakang, Wang, Zihan, Chen, Junzhou, Ren, Yilong, Gao, Bolin, Lv, Zhihan
Road ponding, a prevalent traffic hazard, poses a serious threat to road safety by causing vehicles to lose control and leading to accidents ranging from minor fender benders to severe collisions. Existing technologies struggle to accurately identify
Externí odkaz:
http://arxiv.org/abs/2410.16999
Unsupervised Domain Adaptation (UDA) aims to adapt a model trained on a labeled source domain to an unlabeled target domain by addressing the domain shift. Existing Unsupervised Domain Adaptation (UDA) methods often fall short in fully leveraging con
Externí odkaz:
http://arxiv.org/abs/2410.08023
Autor:
Zhang, Ronghui, Zou, Runzong, Zhao, Yue, Zhang, Zirui, Chen, Junzhou, Cao, Yue, Hu, Chuan, Song, Houbing
Attention mechanisms, particularly channel attention, have become highly influential in numerous computer vision tasks. Despite their effectiveness, many existing methods primarily focus on optimizing performance through complex attention modules app
Externí odkaz:
http://arxiv.org/abs/2410.07860
Autor:
Chen, Junzhou, Zhang, Zirui, Yu, Jing, Huang, Heqiang, Zhang, Ronghui, Xu, Xuemiao, Sheng, Bin, Yan, Hong
Driver distraction remains a leading cause of traffic accidents, posing a critical threat to road safety globally. As intelligent transportation systems evolve, accurate and real-time identification of driver distraction has become essential. However
Externí odkaz:
http://arxiv.org/abs/2409.05587
This article presents Appformer, a novel mobile application prediction framework inspired by the efficiency of Transformer-like architectures in processing sequential data through self-attention mechanisms. Combining a Multi-Modal Data Progressive Fu
Externí odkaz:
http://arxiv.org/abs/2407.19414
Publikováno v:
Journal of Aeronautical Materials, Vol 40, Iss 1, Pp 1-11 (2020)
Aluminum-lithium alloys have formed a perfect material system with high specific strength, high toughness and high damage tolerance resistance after the development of three generations. It is attractive to replace the traditional aluminum alloys owi
Externí odkaz:
https://doaj.org/article/c9ff8ed93df14f44a77a235fbbbb13c7
Publikováno v:
Journal of Aeronautical Materials, Vol 38, Iss 3, Pp 20-25 (2018)
The 7050 aluminum alloy samples were prepared from as-atomized 7050 aluminum alloy powder through cryomilling, hot isostatic pressing, hot extrusion and T6 heat treatment. The influence of cryomilling on morphology, grain size and microscopic strain
Externí odkaz:
https://doaj.org/article/44bf11a655d944aa927fb346c96a693f