Zobrazeno 1 - 10
of 417
pro vyhledávání: '"Wang, JiYuan"'
Autor:
Lin, Youfang, Fu, Jinji, Wen, Haomin, Wang, Jiyuan, Wei, Zhenjie, Qiang, Yuting, Mao, Xiaowei, Wu, Lixia, Hu, Haoyuan, Liang, Yuxuan, Wan, Huaiyu
In Location-Based Services (LBS), such as food delivery, a fundamental task is segmenting Areas of Interest (AOIs), aiming at partitioning the urban geographical spaces into non-overlapping regions. Traditional AOI segmentation algorithms primarily r
Externí odkaz:
http://arxiv.org/abs/2412.05437
Many symptoms of poor performance in big data analytics such as computational skews, data skews, and memory skews are input dependent. However, due to the lack of inputs that can trigger such performance symptoms, it is hard to debug and test big dat
Externí odkaz:
http://arxiv.org/abs/2412.04687
Continuous electroencephalography (EEG) signals are widely used in affective brain-computer interface (aBCI) applications. However, not all continuously collected EEG signals are relevant or meaningful to the task at hand (e.g., wondering thoughts).
Externí odkaz:
http://arxiv.org/abs/2408.12121
Publikováno v:
Chaos, Solitons and Fractals 184, 114979 (2024)
We study the ground-state properties of dipolar spin-1/2 Bose-Einstein condensates with quantum fluctuations and Rashba spin-orbit coupling (SOC). The combined effects of dipole-dipole interaction (DDI), SOC, and Lee-Huang-Yang (LHY) correction induc
Externí odkaz:
http://arxiv.org/abs/2405.04149
Compiler technologies in deep learning and domain-specific hardware acceleration are increasingly adopting extensible compiler frameworks such as Multi-Level Intermediate Representation (MLIR) to facilitate more efficient development. With MLIR, comp
Externí odkaz:
http://arxiv.org/abs/2404.16947
Recently, diffusion-based depth estimation methods have drawn widespread attention due to their elegant denoising patterns and promising performance. However, they are typically unreliable under adverse conditions prevalent in real-world scenarios, s
Externí odkaz:
http://arxiv.org/abs/2404.09831
The integration of human emotions into multimedia applications shows great potential for enriching user experiences and enhancing engagement across various digital platforms. Unlike traditional methods such as questionnaires, facial expressions, and
Externí odkaz:
http://arxiv.org/abs/2404.09559
The rapid development of Large Language Models (LLMs) has facilitated a variety of applications from different domains. In this technical report, we explore the integration of LLMs and the popular academic writing tool, Overleaf, to enhance the effic
Externí odkaz:
http://arxiv.org/abs/2403.09733
Publikováno v:
ICRA 2024
Depth estimation models have shown promising performance on clear scenes but fail to generalize to adverse weather conditions due to illumination variations, weather particles, etc. In this paper, we propose WeatherDepth, a self-supervised robust dep
Externí odkaz:
http://arxiv.org/abs/2310.05556
Autor:
Huang, Jing a, b, 1, Liang, Yan c, 1, Wang, Jiyuan a, b, Shan, Yi a, b, Zhao, Cheng a, b, Li, Qiongge a, b, Dong, Huiqing c, Lu, Jie a, b, ⁎
Publikováno v:
In Brain Research 15 January 2025 1847
