Zobrazeno 1 - 10
of 1 920
pro vyhledávání: '"SHANG, LEI"'
In the field of human-centric personalized image generation, the adapter-based method obtains the ability to customize and generate portraits by text-to-image training on facial data. This allows for identity-preserved personalization without additio
Externí odkaz:
http://arxiv.org/abs/2410.12312
Autor:
Qin, Ziheng, Xu, Zhaopan, Zhou, Yukun, Zheng, Zangwei, Cheng, Zebang, Tang, Hao, Shang, Lei, Sun, Baigui, Peng, Xiaojiang, Timofte, Radu, Yao, Hongxun, Wang, Kai, You, Yang
Deep learning benefits from the growing abundance of available data. Meanwhile, efficiently dealing with the growing data scale has become a challenge. Data publicly available are from different sources with various qualities, and it is impractical t
Externí odkaz:
http://arxiv.org/abs/2405.18347
Subject-driven generation has garnered significant interest recently due to its ability to personalize text-to-image generation. Typical works focus on learning the new subject's private attributes. However, an important fact has not been taken serio
Externí odkaz:
http://arxiv.org/abs/2403.06775
Publikováno v:
电力工程技术, Vol 43, Iss 6, Pp 214-222 (2024)
Grid-forming energy storage can not only have the conventional energy storage function, but also be able to improve the system inertia to meet the demand for rapid frequency and voltage regulation of microgrid with high renewable penetration. Therefo
Externí odkaz:
https://doaj.org/article/6c9f9a2e72e146a1b9cbdf98fdcc540f
Autor:
Yadong Li, Ronghua Xu, Qianying Han, Shang Lei, Congli Ma, Jingyi Qi, Yingliang Liu, Hongjie Wang
Publikováno v:
Crop Journal, Vol 12, Iss 5, Pp 1496-1501 (2024)
Soil salinity seriously affects the utilization of farmland and threatens the crop production. Here, a selenium-nitrogen-co-doped carbon dots was developed, which increased rice seedling growth and alleviated its inhibition by salt stress by foliar s
Externí odkaz:
https://doaj.org/article/af80433bc0b3420db9e60b291e743bb8
Autor:
Liu, Yang, Yu, Cheng, Shang, Lei, He, Yongyi, Wu, Ziheng, Wang, Xingjun, Xu, Chao, Xie, Haoyu, Wang, Weida, Zhao, Yuze, Zhu, Lin, Cheng, Chen, Chen, Weitao, Yao, Yuan, Zhou, Wenmeng, Xu, Jiaqi, Wang, Qiang, Chen, Yingda, Xie, Xuansong, Sun, Baigui
Recent advancement in personalized image generation have unveiled the intriguing capability of pre-trained text-to-image models on learning identity information from a collection of portrait images. However, existing solutions are vulnerable in produ
Externí odkaz:
http://arxiv.org/abs/2308.14256
Autor:
Qin, Ziheng, Wang, Kai, Zheng, Zangwei, Gu, Jianyang, Peng, Xiangyu, Xu, Zhaopan, Zhou, Daquan, Shang, Lei, Sun, Baigui, Xie, Xuansong, You, Yang
Data pruning aims to obtain lossless performances with less overall cost. A common approach is to filter out samples that make less contribution to the training. This could lead to gradient expectation bias compared to the original data. To solve thi
Externí odkaz:
http://arxiv.org/abs/2303.04947
Autor:
Shang, Lei, Huang, Mouxiao, Shi, Wu, Liu, Yuchen, Liu, Yang, Wang, Fei, Sun, Baigui, Xie, Xuansong, Qiao, Yu
Data uncertainty is commonly observed in the images for face recognition (FR). However, deep learning algorithms often make predictions with high confidence even for uncertain or irrelevant inputs. Intuitively, FR algorithms can benefit from both the
Externí odkaz:
http://arxiv.org/abs/2212.01015
Autor:
Zang, Zelin, Cheng, Shenghui, Lu, Linyan, Xia, Hanchen, Li, Liangyu, Sun, Yaoting, Xu, Yongjie, Shang, Lei, Sun, Baigui, Li, Stan Z.
Dimension reduction (DR) is commonly utilized to capture the intrinsic structure and transform high-dimensional data into low-dimensional space while retaining meaningful properties of the original data. It is used in various applications, such as im
Externí odkaz:
http://arxiv.org/abs/2211.15478
Unsupervised domain adaptation (UDA) has proven to be highly effective in transferring knowledge from a label-rich source domain to a label-scarce target domain. However, the presence of additional novel categories in the target domain has led to the
Externí odkaz:
http://arxiv.org/abs/2211.11262