Zobrazeno 1 - 10
of 406
pro vyhledávání: '"Qiu, Hang"'
The confluence of the advancement of Autonomous Vehicles (AVs) and the maturity of Vehicle-to-Everything (V2X) communication has enabled the capability of cooperative connected and automated vehicles (CAVs). Building on top of cooperative perception,
Externí odkaz:
http://arxiv.org/abs/2403.17916
Autor:
Zhou, Yunsong, Huang, Linyan, Bu, Qingwen, Zeng, Jia, Li, Tianyu, Qiu, Hang, Zhu, Hongzi, Guo, Minyi, Qiao, Yu, Li, Hongyang
Embodied scene understanding serves as the cornerstone for autonomous agents to perceive, interpret, and respond to open driving scenarios. Such understanding is typically founded upon Vision-Language Models (VLMs). Nevertheless, existing VLMs are re
Externí odkaz:
http://arxiv.org/abs/2403.04593
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 7, p e18527 (2020)
BackgroundAn OHC online health community (OHC) is an interactive platform for virtual communication between patients and physicians. Patients can typically search, seek, and share their experience and rate physicians, who may be involved in giving ad
Externí odkaz:
https://doaj.org/article/61636ffcb8554de7b0b38c10c3519d8b
Autor:
Chen, Kan, Ge, Runzhou, Qiu, Hang, AI-Rfou, Rami, Qi, Charles R., Zhou, Xuanyu, Yang, Zoey, Ettinger, Scott, Sun, Pei, Leng, Zhaoqi, Baniodeh, Mustafa, Bogun, Ivan, Wang, Weiyue, Tan, Mingxing, Anguelov, Dragomir
Widely adopted motion forecasting datasets substitute the observed sensory inputs with higher-level abstractions such as 3D boxes and polylines. These sparse shapes are inferred through annotating the original scenes with perception systems' predicti
Externí odkaz:
http://arxiv.org/abs/2304.03834
Autor:
Liu, Chengxu, Li, Bin, Ge, Yongheng, Jiao, Wen-He, Xi, Chuanying, Liu, Yi, Xu, Chunqiang, Lu, Qi, Li, Yunlong, Qiu, Hang-Qiang, Zhu, Qin-Qing, Ren, Zhi, Zhu, Ziming, Qian, Dong, Ke, Xianglin, Xu, Xiaofeng
The quest for quantum materials with diverse symmetry-protected topological states has been the focus of recent research interest, primarily due to their fascinating physical properties and the potential technological utility. In this work, we report
Externí odkaz:
http://arxiv.org/abs/2205.04307
Publikováno v:
CVPR 2022
Optical sensors and learning algorithms for autonomous vehicles have dramatically advanced in the past few years. Nonetheless, the reliability of today's autonomous vehicles is hindered by the limited line-of-sight sensing capability and the brittlen
Externí odkaz:
http://arxiv.org/abs/2205.02222
Autor:
Qiu, Hang, Huang, Pohan, Asavisanu, Namo, Liu, Xiaochen, Psounis, Konstantinos, Govindan, Ramesh
Publikováno v:
ACM Mobisys 2022
Autonomous vehicles use 3D sensors for perception. Cooperative perception enables vehicles to share sensor readings with each other to improve safety. Prior work in cooperative perception scales poorly even with infrastructure support. AutoCast enabl
Externí odkaz:
http://arxiv.org/abs/2112.14947
Autonomous vehicles (AVs) must interact with a diverse set of human drivers in heterogeneous geographic areas. Ideally, fleets of AVs should share trajectory data to continually re-train and improve trajectory forecasting models from collective exper
Externí odkaz:
http://arxiv.org/abs/2112.00956
Autor:
Qiu, Hang, Vavelidou, Ioanna, Li, Jian, Pergament, Evgenya, Warden, Pete, Chinchali, Sandeep, Asgar, Zain, Katti, Sachin
Publikováno v:
MLSys 2022
Benefiting from expanding cloud infrastructure, deep neural networks (DNNs) today have increasingly high performance when trained in the cloud. Researchers spend months of effort competing for an extra few percentage points of model accuracy. However
Externí odkaz:
http://arxiv.org/abs/2111.04779
Publikováno v:
In Computer Methods and Programs in Biomedicine June 2024 249