Zobrazeno 1 - 10
of 1 852
pro vyhledávání: '"Zida An"'
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionEEG-based emotion recognition has gradually become a new research direction, known as affective Brain-Computer Interface (aBCI), which has huge application potential in human-computer interaction and neuroscience. However, how to extract
Externí odkaz:
https://doaj.org/article/b53ef0c4970f473797ead2f3e2258019
Autor:
Yuzhang Wen, Fengxin Sun, Zhenning Xie, Mengqi Zhang, Zida An, Bing Liu, Yuning Sun, Fei Wang, Yupeng Mao
Publikováno v:
iScience, Vol 27, Iss 4, Pp 109615- (2024)
Summary: In the smart era, big data analysis based on sensor units is important in intelligent motion. In this study, a dance sports and injury monitoring system (DIMS) based on a recyclable flexible triboelectric nanogenerator (RF-TENG) sensor modul
Externí odkaz:
https://doaj.org/article/dd1eed7a29594e00a4fdba3f7dbcddd0
Autor:
Chen, Xu, Cheng, Zida, Pan, Yuangang, Xiao, Shuai, Liu, Xiaoming, Lan, Jinsong, Liu, Qingwen, Tsang, Ivor W.
Existing click-through rate (CTR) prediction works have studied the role of feature interaction through a variety of techniques. Each interaction technique exhibits its own strength, and solely using one type could constrain the model's capability to
Externí odkaz:
http://arxiv.org/abs/2411.13057
We prove that in regular $F$-finite rings of positive characteristic, the Bernstein-Sato root set of the tensor product of ideals is the union of their respective Bernstein-Sato root sets. Moreover, by computing some special $F$-thresholds, we provid
Externí odkaz:
http://arxiv.org/abs/2410.20188
The detection of malicious social bots has become a crucial task, as bots can be easily deployed and manipulated to spread disinformation, promote conspiracy messages, and more. Most existing approaches utilize graph neural networks (GNNs)to capture
Externí odkaz:
http://arxiv.org/abs/2410.05356
Autor:
Wu, Zida, Mehta, Ankur
A crucial challenge in decentralized systems is state estimation in the presence of unknown inputs, particularly within heterogeneous sensor networks with dynamic topologies. While numerous consensus algorithms have been introduced, they often requir
Externí odkaz:
http://arxiv.org/abs/2410.00272
With the rapid advancement of generative AI, multimodal deepfakes, which manipulate both audio and visual modalities, have drawn increasing public concern. Currently, deepfake detection has emerged as a crucial strategy in countering these growing th
Externí odkaz:
http://arxiv.org/abs/2405.08838
Autor:
Gu, Hongyan, Yan, Zihan, Alvi, Ayesha, Day, Brandon, Yang, Chunxu, Wu, Zida, Magaki, Shino, Haeri, Mohammad, Chen, Xiang 'Anthony'
The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for doctors' annotations in AI development. However, collecting high-quality annotations from doctors is costly and time-consuming, creating a bottleneck in A
Externí odkaz:
http://arxiv.org/abs/2404.01656
We report structural and electronic properties of Na$_2$Ni$_3$S$_4$, a quasi-two-dimensional compound composed of alternating layers of [Ni$_3$S$_4$]$^{2-}$ and Na$^{+}$. The compound features a remarkable Ni-based kagome lattice with a square planar
Externí odkaz:
http://arxiv.org/abs/2403.08456
Autor:
Wu, Zida, Lauriere, Mathieu, Chua, Samuel Jia Cong, Geist, Matthieu, Pietquin, Olivier, Mehta, Ankur
Mean Field Games (MFGs) have the ability to handle large-scale multi-agent systems, but learning Nash equilibria in MFGs remains a challenging task. In this paper, we propose a deep reinforcement learning (DRL) algorithm that achieves population-depe
Externí odkaz:
http://arxiv.org/abs/2403.03552