Zobrazeno 1 - 10
of 2 019
pro vyhledávání: '"CHEN Xiaogang"'
Brain-computer interfaces (BCIs) offer a way to interact with computers without relying on physical movements. Non-invasive electroencephalography (EEG)-based visual BCIs, known for efficient speed and calibration ease, face limitations in continuous
Externí odkaz:
http://arxiv.org/abs/2311.12592
Autor:
Miao, Yining, Shi, Nanlin, Huang, Changxing, Song, Yonghao, Chen, Xiaogang, Wang, Yijun, Gao, Xiaorong
The ultimate goal of brain-computer interfaces (BCIs) based on visual modulation paradigms is to achieve high-speed performance without the burden of extensive calibration. Code-modulated visual evoked potential-based BCIs (cVEP-BCIs) modulated by br
Externí odkaz:
http://arxiv.org/abs/2311.11596
Autor:
Sun, Yike, Chen, Xiaogang, Liu, Bingchuan, Liang, Liyan, Wang, Yijun, Gao, Shangkai, Gao, Xiaorong
Brain-computer interface (BCI) technology is an interdisciplinary field that allows individuals to connect with the external world. The performance of BCI systems relies predominantly on the advancements of signal acquisition technology. This paper a
Externí odkaz:
http://arxiv.org/abs/2308.16102
Autor:
Shi, Nanlin, Miao, Yining, Huang, Changxing, Li, Xiang, Song, Yonghao, Chen, Xiaogang, Wang, Yijun, Gao, Xiaorong
The mission of visual brain-computer interfaces (BCIs) is to enhance information transfer rate (ITR) to reach high speed towards real-life communication. Despite notable progress, noninvasive visual BCIs have encountered a plateau in ITRs, leaving it
Externí odkaz:
http://arxiv.org/abs/2308.13232
Target tracking and trajectory modeling have important applications in surveillance video analysis and have received great attention in the fields of road safety and community security. In this work, we propose a lightweight real-time video analysis
Externí odkaz:
http://arxiv.org/abs/2305.08418
Autor:
Qian, Xingyu, Yuemaier, Aximu, Liang, Longfei, Yang, Wen-Chi, Chen, Xiaogang, Li, Shunfen, Dai, Weibang, Song, Zhitang
We propose an adaptive multi-agent clustering recognition system that can be self-supervised driven, based on a temporal sequences continuous learning mechanism with adaptability. The system is designed to use some different functional agents to buil
Externí odkaz:
http://arxiv.org/abs/2212.07646
Autor:
Zhang, Yan, Wang, Yanting, Zhu, Peiyuan, Jing, Siyuan, Li, Jiana, Wanger, Thomas Cherico, Liu, Weiping, Liu, Kai, Chen, Xiaogang, Li, Ling
Publikováno v:
In Environmental Pollution 15 December 2024 363 Part 1
Autor:
Chen, Yuzhen, Bai, Jiawen, Shi, Nanlin, Jiang, Yunpeng, Chen, Xiaogang, Ku, Yixuan, Gao, Xiaorong
Publikováno v:
In NeuroImage 1 December 2024 303
Autor:
Li, Jinguang, He, Jingqi, Ren, Honghong, Li, Zongchang, Ma, Xiaoqian, Yuan, Liu, Ouyang, Lijun, Liao, Aijun, Peng, Huiqing, He, Ying, Tang, Jinsong, Chen, Xiaogang
Publikováno v:
In Schizophrenia Research December 2024 274:517-525
Publikováno v:
In Sensors and Actuators: A. Physical 1 December 2024 379