Zobrazeno 1 - 10
of 24 716
pro vyhledávání: '"Xu,Jie"'
This paper considers a multi-functional orthogonal frequency division multiplexing (OFDM) system with integrated sensing, communication, and powering (ISCAP), in which a multi-antenna base station (BS) transmits OFDM signals to simultaneously deliver
Externí odkaz:
http://arxiv.org/abs/2408.14156
In practical federated learning (FL) systems, the presence of malicious Byzantine attacks and data heterogeneity often introduces biases into the learning process. However, existing Byzantine-robust methods typically only achieve a compromise between
Externí odkaz:
http://arxiv.org/abs/2408.09539
Federated Learning (FL) is a distributed machine learning approach that enables devices to collaboratively train models without sharing their local data, ensuring user privacy and scalability. However, applying FL to real-world data presents challeng
Externí odkaz:
http://arxiv.org/abs/2408.06549
For both humans and robots, the sense of touch, known as tactile sensing, is critical for performing contact-rich manipulation tasks. Three key challenges in robotic tactile sensing are 1) interpreting sensor signals, 2) generating sensor signals in
Externí odkaz:
http://arxiv.org/abs/2408.06506
This paper studies a near-field integrated sensing and communication (ISAC) system with extremely large-scale antenna array (ELAA), in which a base station (BS) deployed with enormous number of antennas transmits wireless signals to communicate with
Externí odkaz:
http://arxiv.org/abs/2407.17237
This paper investigates the transmission of three-dimensional (3D) human face content for immersive communication over a rate-constrained transmitter-receiver link. We propose a new framework named NeRF-SeCom, which leverages neural radiance fields (
Externí odkaz:
http://arxiv.org/abs/2407.13992
Autor:
Tang, Bingjie, Akinola, Iretiayo, Xu, Jie, Wen, Bowen, Handa, Ankur, Van Wyk, Karl, Fox, Dieter, Sukhatme, Gaurav S., Ramos, Fabio, Narang, Yashraj
Robotic assembly for high-mixture settings requires adaptivity to diverse parts and poses, which is an open challenge. Meanwhile, in other areas of robotics, large models and sim-to-real have led to tremendous progress. Inspired by such work, we pres
Externí odkaz:
http://arxiv.org/abs/2407.08028
Autor:
Yu, Wenlu, Xu, Jie, Zhao, Chengwei, Zhao, Lijun, Nguyen, Thien-Minh, Yuan, Shenghai, Bai, Mingming, Xie, Lihua
LiDAR odometry is a pivotal technology in the fields of autonomous driving and autonomous mobile robotics. However, most of the current works focus on nonlinear optimization methods, and still existing many challenges in using the traditional Iterati
Externí odkaz:
http://arxiv.org/abs/2407.02190
Autor:
Liu, Mianxin, Ding, Jinru, Xu, Jie, Hu, Weiguo, Li, Xiaoyang, Zhu, Lifeng, Bai, Zhian, Shi, Xiaoming, Wang, Benyou, Song, Haitao, Liu, Pengfei, Zhang, Xiaofan, Wang, Shanshan, Li, Kang, Wang, Haofen, Ruan, Tong, Huang, Xuanjing, Sun, Xin, Zhang, Shaoting
Ensuring the general efficacy and goodness for human beings from medical large language models (LLM) before real-world deployment is crucial. However, a widely accepted and accessible evaluation process for medical LLM, especially in the Chinese cont
Externí odkaz:
http://arxiv.org/abs/2407.10990
This paper exploits the networked integrated sensing and communications (ISAC) to support low-altitude economy (LAE), in which a set of networked ground base stations (GBSs) cooperatively transmit joint information and sensing signals to communicate
Externí odkaz:
http://arxiv.org/abs/2406.16946