Zobrazeno 1 - 10
of 11 433
pro vyhledávání: '"An, Ruixin"'
Autor:
Huang, Chao, Xiao, Huichen, Chen, Chen, Chen, Chunyan, Zhao, Yi, Du, Shiyu, Zhang, Yiming, Sha, He, Gu, Ruixin
As the application of large language models in various fields continues to expand, materials science also ushers in opportunities for AI-driven innovation. The traditional way of relying on manual search for materials science-related information is n
Externí odkaz:
http://arxiv.org/abs/2411.08728
Autor:
Lia, Ruixin, Zhaoa, Guoxu, Muir, Dylan Richard, Ling, Yuya, Burelo, Karla, Khoei, Mina, Wang, Dong, Xing, Yannan, Qiao, Ning
Publikováno v:
Computers in Biology and Medicine(2024), 183, 109225
Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject presents a challenge to existing technologies aimed at providing timely and efficient diagnosis. In this study, we aimed to detect interictal and ictal p
Externí odkaz:
http://arxiv.org/abs/2410.16613
Decompilation, the process of converting machine-level code into readable source code, plays a critical role in reverse engineering. Given that the main purpose of decompilation is to facilitate code comprehension in scenarios where the source code i
Externí odkaz:
http://arxiv.org/abs/2409.20343
Very low-resolution face recognition is challenging due to the serious loss of informative facial details in resolution degradation. In this paper, we propose a generative-discriminative representation distillation approach that combines generative r
Externí odkaz:
http://arxiv.org/abs/2409.06371
Autor:
Yu, Jifan, Zhang, Zheyuan, Zhang-li, Daniel, Tu, Shangqing, Hao, Zhanxin, Li, Rui Miao, Li, Haoxuan, Wang, Yuanchun, Li, Hanming, Gong, Linlu, Cao, Jie, Lin, Jiayin, Zhou, Jinchang, Qin, Fei, Wang, Haohua, Jiang, Jianxiao, Deng, Lijun, Zhan, Yisi, Xiao, Chaojun, Dai, Xusheng, Yan, Xuan, Lin, Nianyi, Zhang, Nan, Ni, Ruixin, Dang, Yang, Hou, Lei, Zhang, Yu, Han, Xu, Li, Manli, Li, Juanzi, Liu, Zhiyuan, Liu, Huiqin, Sun, Maosong
Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to reach a broader audience has sparked extensive discussion and widesprea
Externí odkaz:
http://arxiv.org/abs/2409.03512
Recognizing objects in low-resolution images is a challenging task due to the lack of informative details. Recent studies have shown that knowledge distillation approaches can effectively transfer knowledge from a high-resolution teacher model to a l
Externí odkaz:
http://arxiv.org/abs/2409.02555
Low-resolution face recognition is a challenging task due to the missing of informative details. Recent approaches based on knowledge distillation have proven that high-resolution clues can well guide low-resolution face recognition via proper knowle
Externí odkaz:
http://arxiv.org/abs/2409.02049
Autor:
Tan, Zhuolin, Gao, Chenqiang, Qin, Anyong, Chen, Ruixin, Song, Tiecheng, Yang, Feng, Meng, Deyu
Analyzing student actions is an important and challenging task in educational research. Existing efforts have been hampered by the lack of accessible datasets to capture the nuanced action dynamics in classrooms. In this paper, we present a new multi
Externí odkaz:
http://arxiv.org/abs/2409.00926
Autor:
Guan, Zhihao, Liu, Ruixin, Yuan, Zejian, Liu, Ao, Tang, Kun, Zhou, Tong, Li, Erlong, Zheng, Chao, Mei, Shuqi
As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict demands for precision. In this paper, an end-to-end flexible and hierarc
Externí odkaz:
http://arxiv.org/abs/2408.07163
Long-term time series forecasting (LTSF) has been widely applied in finance, traffic prediction, and other domains. Recently, patch-based transformers have emerged as a promising approach, segmenting data into sub-level patches that serve as input to
Externí odkaz:
http://arxiv.org/abs/2408.02279