Zobrazeno 1 - 10
of 532
pro vyhledávání: '"Li Yongwei"'
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 7, Pp 127-132 (2024)
Objective The thickness of diaphragm walls significantly affects the amount and mode of foundation pit deformation, thin-walled diaphragm walls are especially sensitive to excavation and edge loads of foundation pit. Therefore, it is necessary to stu
Externí odkaz:
https://doaj.org/article/3e3910700c6a40b7be3e7945b68782ea
Publikováno v:
AIP Advances, Vol 14, Iss 4, Pp 045002-045002-17 (2024)
For meeting the requirements of tactical missiles seeking miniaturized launch devices for storage, transportation, and launch, a tube-launched missile wing is adopted, which folds before launch and quickly unfolds after launch. As a structure install
Externí odkaz:
https://doaj.org/article/3b16095c7c9f4ed798afb2edd7c126da
Autor:
Qi, Xin, Fu, Ruibo, Wen, Zhengqi, Tao, Jianhua, Shi, Shuchen, Lu, Yi, Wang, Zhiyong, Wang, Xiaopeng, Xie, Yuankun, Liu, Yukun, Li, Guanjun, Liu, Xuefei, Li, Yongwei
In the current era of Artificial Intelligence Generated Content (AIGC), a Low-Rank Adaptation (LoRA) method has emerged. It uses a plugin-based approach to learn new knowledge with lower parameter quantities and computational costs, and it can be plu
Externí odkaz:
http://arxiv.org/abs/2408.10852
Autor:
Wang, Zhiyong, Wang, Xiaopeng, Xie, Yuankun, Fu, Ruibo, Wen, Zhengqi, Tao, Jianhua, Liu, Yukun, Li, Guanjun, Qi, Xin, Lu, Yi, Liu, Xuefei, Li, Yongwei
In the field of deepfake detection, previous studies focus on using reconstruction or mask and prediction methods to train pre-trained models, which are then transferred to fake audio detection training where the encoder is used to extract features,
Externí odkaz:
http://arxiv.org/abs/2408.10849
Autor:
Zheng, Yu, Hu, Quanxin, Ji, Haijiao, Timoshuk, Igor, Xu, Hanxiang, Li, Yongwei, Gao, Ye, Yu, Xin, Wu, Rui, Lu, Xingye, Grinenko, Vadim, Babaev, Egor, Yuan, Noah F. Q., Lv, Baiqing, Yim, Chi-Ming, Ding, Hong
Magnetic field is expelled from a superconductor, unless it forms quantum vortices, consisting of a core singularity with current circulating around it. The London quantization condition implies that there is one core singularity per quantum of magne
Externí odkaz:
http://arxiv.org/abs/2407.18610
Autor:
Cai, Cong, Liang, Shan, Liu, Xuefei, Zhu, Kang, Wen, Zhengqi, Tao, Jianhua, Xie, Heng, Cui, Jizhou, Ma, Yiming, Cheng, Zhenhua, Xu, Hanzhe, Fu, Ruibo, Liu, Bin, Li, Yongwei
Deception detection has garnered increasing attention in recent years due to the significant growth of digital media and heightened ethical and security concerns. It has been extensively studied using multimodal methods, including video, audio, and t
Externí odkaz:
http://arxiv.org/abs/2407.12274
Autor:
Lu, Yi, Xie, Yuankun, Fu, Ruibo, Wen, Zhengqi, Tao, Jianhua, Wang, Zhiyong, Qi, Xin, Liu, Xuefei, Li, Yongwei, Liu, Yukun, Wang, Xiaopeng, Shi, Shuchen
With the proliferation of Large Language Model (LLM) based deepfake audio, there is an urgent need for effective detection methods. Previous deepfake audio generation methods typically involve a multi-step generation process, with the final step usin
Externí odkaz:
http://arxiv.org/abs/2406.08112
Autor:
Shi, Shuchen, Fu, Ruibo, Wen, Zhengqi, Tao, Jianhua, Wang, Tao, Qiang, Chunyu, Lu, Yi, Qi, Xin, Liu, Xuefei, Liu, Yukun, Li, Yongwei, Wang, Zhiyong, Wang, Xiaopeng
Text-to-Audio (TTA) aims to generate audio that corresponds to the given text description, playing a crucial role in media production. The text descriptions in TTA datasets lack rich variations and diversity, resulting in a drop in TTA model performa
Externí odkaz:
http://arxiv.org/abs/2406.04683
Autor:
Wang, Zhiyong, Fu, Ruibo, Wen, Zhengqi, Xie, Yuankun, Liu, Yukun, Wang, Xiaopeng, Liu, Xuefei, Li, Yongwei, Tao, Jianhua, Lu, Yi, Qi, Xin, Shi, Shuchen
Although current fake audio detection approaches have achieved remarkable success on specific datasets, they often fail when evaluated with datasets from different distributions. Previous studies typically address distribution shift by focusing on us
Externí odkaz:
http://arxiv.org/abs/2406.03237
Autor:
Wang, Xiaopeng, Fu, Ruibo, Wen, Zhengqi, Wang, Zhiyong, Xie, Yuankun, Liu, Yukun, Tao, Jianhua, Liu, Xuefei, Li, Yongwei, Qi, Xin, Lu, Yi, Shi, Shuchen
The generalization of Fake Audio Detection (FAD) is critical due to the emergence of new spoofing techniques. Traditional FAD methods often focus solely on distinguishing between genuine and known spoofed audio. We propose a Genuine-Focused Learning
Externí odkaz:
http://arxiv.org/abs/2406.03247