Výsledky vyhledávání - "Liu, Kaixuan"

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FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Object Detection

Autor: Hu, Chunyong, Zheng, Hang, Li, Kun, Xu, Jianyun, Mao, Weibo, Luo, Maochun, Wang, Lingxuan, Chen, Mingxia, Peng, Qihao, Liu, Kaixuan, Zhao, Yiru, Hao, Peihan, Liu, Minzhe, Yu, Kaicheng

Multi-sensor modal fusion has demonstrated strong advantages in 3D object detection tasks. However, existing methods that fuse multi-modal features require transforming features into the bird's eye view space and may lose certain information on Z-axi

Externí odkaz: http://arxiv.org/abs/2309.05257

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Akademický článek

Quantifying the Contributions of Vegetation Dynamics and Climate Factors to the Enhancement of Vegetation Productivity in Northern China (2001–2020).

Autor: Liu, Kaixuan^1,2 (AUTHOR) liukaixuan@nieer.ac.cn, Wang, Xufeng¹ (AUTHOR) wangxufeng@lzb.ac.cn, Wang, Haibo¹ (AUTHOR) whb@lzb.ac.cn

Publikováno v: Remote Sensing. Oct2024, Vol. 16 Issue 20, p3813. 18p.

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INT: Towards Infinite-frames 3D Detection with An Efficient Framework

Autor: Xu, Jianyun, Miao, Zhenwei, Zhang, Da, Pan, Hongyu, Liu, Kaixuan, Hao, Peihan, Zhu, Jun, Sun, Zhengyang, Li, Hongmin, Zhan, Xin

It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their

Externí odkaz: http://arxiv.org/abs/2209.15215

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Convolutional Neural Networks with A Topographic Representation Module for EEG-Based Brain-Computer Interfaces

Autor: Liang, Xinbin, Liu, Yaru, Yu, Yang, Liu, Kaixuan, Liu, Yadong, Zhou, Zongtan

Objective: Convolutional Neural Networks (CNNs) have shown great potential in the field of Brain-Computer Interfaces (BCIs). The raw Electroencephalogram (EEG) signal is usually represented as 2-Dimensional (2-D) matrix composed of channels and time

Externí odkaz: http://arxiv.org/abs/2208.10708

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EEG-Based Detection of Braking Intention During Simulated Driving

Autor: Liang, Xinbin, Yu, Yang, Liu, Yadong, Liu, Kaixuan, Liu, Yaru, Zhou, Zongtan

Accurately detecting and identifying drivers' braking intention is the basis of man-machine driving. In this paper, we proposed an electroencephalographic (EEG)-based braking intention measurement strategy. We used the Car Learning to Act (Carla) pla

Externí odkaz: http://arxiv.org/abs/2207.12669

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