Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Zhang, Xiaofei"'
Autor:
Zhang, Xiaofei, Li, Yining, Wang, Jinping, Qin, Xiangyi, Shen, Ying, Fan, Zhengping, Tan, Xiaojun
Perception systems of autonomous vehicles are susceptible to occlusion, especially when examined from a vehicle-centric perspective. Such occlusion can lead to overlooked object detections, e.g., larger vehicles such as trucks or buses may create bli
Externí odkaz:
http://arxiv.org/abs/2407.21581
Autor:
Li, Baihong, Wang, Zhuo-zhuo, Li, Qi-qi, Chen, Changhua, Yuan, Boxin, Zhai, Yiwei, Jin, Rui-Bo, Zhang, Xiaofei
We theoretically propose a multiparameter cascaded quantum interferometer in which a two-input and two-output setup is obtained by concatenating 50:50 beam splitters with n independent and adjustable time delays. A general method for deriving the coi
Externí odkaz:
http://arxiv.org/abs/2404.07509
Autor:
Xiong, Haoyi, Li, Xuhong, Zhang, Xiaofei, Chen, Jiamin, Sun, Xinhao, Li, Yuchen, Sun, Zeyi, Du, Mengnan
Given the complexity and lack of transparency in deep neural networks (DNNs), extensive efforts have been made to make these systems more interpretable or explain their behaviors in accessible terms. Unlike most reviews, which focus on algorithmic an
Externí odkaz:
http://arxiv.org/abs/2401.04374
In recent years, privacy-preserving machine learning algorithms have attracted increasing attention because of their important applications in many scientific fields. However, in the literature, most privacy-preserving algorithms demand learning obje
Externí odkaz:
http://arxiv.org/abs/2401.01294
Autor:
Li, Baihong, Chen, Changhua, Yuan, Boxin, Zhang, Xiaofei, Dong, Ruifang, Zhang, Shougang, Jin, Rui-Bo
Entangled photons (biphotons) in the time-frequency degree of freedom play a crucial role in both foundational physics and advanced quantum technologies. Fully characterizing them poses a key scientific challenge. Here, we propose a theoretical appro
Externí odkaz:
http://arxiv.org/abs/2311.08164
Autor:
Zhang, Xinyu, Wang, Li, Chen, Jian, Fang, Cheng, Yang, Lei, Song, Ziying, Yang, Guangqi, Wang, Yichen, Zhang, Xiaofei, Li, Jun, Li, Zhiwei, Yang, Qingshan, Zhang, Zhenlin, Ge, Shuzhi Sam
Radar has stronger adaptability in adverse scenarios for autonomous driving environmental perception compared to widely adopted cameras and LiDARs. Compared with commonly used 3D radars, the latest 4D radars have precise vertical resolution and highe
Externí odkaz:
http://arxiv.org/abs/2310.07602
Large language models (LLMs) have become phenomenally surging, since 2018--two decades after introducing context-awareness into computing systems. Through taking into account the situations of ubiquitous devices, users and the societies, context-awar
Externí odkaz:
http://arxiv.org/abs/2309.15074
A prevalent limitation of optimizing over a single objective is that it can be misguided, becoming trapped in local optimum. This can be rectified by Quality-Diversity (QD) algorithms, where a population of high-quality and diverse solutions to a pro
Externí odkaz:
http://arxiv.org/abs/2304.07425
Autor:
Hua, Boyu, Ni, Haoran, Zhu, Qiuming, Wang, Cheng-Xiang, Zhou, Tongtong, Mao, Kai, Bao, Junwei, Zhang, Xiaofei
Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role for reliable communications between UAV and ground terminal. This paper proposes a three-dimensional (3D) non-stationary hybrid model including both large-scale and smal
Externí odkaz:
http://arxiv.org/abs/2210.02245
Autor:
Lian, Xiang, Zhang, Xiaofei
Deep neural network (DNN) and its variants have been extensively used for a wide spectrum of real applications such as image classification, face/speech recognition, fraud detection, and so on. In addition to many important machine learning tasks, as
Externí odkaz:
http://arxiv.org/abs/2206.05778