Zobrazeno 1 - 10
of 1 467
pro vyhledávání: '"QIN Zhan"'
Autor:
Hongdeng Jian, Zhenzhen Yan, Xiangtao Fan, Qin Zhan, Chen Xu, Weijia Bei, Jianhao Xu, Mingrui Huang, Xiaoping Du, Junjie Zhu, Zhimin Tai, Jiangtao Hao, Yanan Hu
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-11 (2024)
Abstract The human thermal stress indices and datasets are vital for promoting public health and reducing negative environmental impacts as global climate change and extreme meteorological events increase. The current thermal indices generally use an
Externí odkaz:
https://doaj.org/article/8c1a104b1ba642ea989781b42e401144
Autor:
Yi Wan, En Li, Zhihao Yu, Jing-Kai Huang, Ming-Yang Li, Ang-Sheng Chou, Yi-Te Lee, Chien-Ju Lee, Hung-Chang Hsu, Qin Zhan, Areej Aljarb, Jui-Han Fu, Shao-Pin Chiu, Xinran Wang, Juhn-Jong Lin, Ya-Ping Chiu, Wen-Hao Chang, Han Wang, Yumeng Shi, Nian Lin, Yingchun Cheng, Vincent Tung, Lain-Jong Li
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-8 (2022)
Chemical vapor deposition enables the scalable production of 2D semiconductors, but the grown materials are usually affected by high defect densities. Here, the authors report a hydroxide vapour phase deposition method to synthesize wafer-scale monol
Externí odkaz:
https://doaj.org/article/b75bdb1edf6c415fa39d0d189ad85c76
Publikováno v:
Big Earth Data, Pp 1-20 (2022)
Unified representation of spatial earth data is an essential scientific issue. The analysis and mining of interdisciplinary spatial earth data resources can help discover hidden scientific knowledge, and even reveal the intrinsic relationship among d
Externí odkaz:
https://doaj.org/article/980e8d3ec1c2449a847a1aec0c43bcf3
Embeddings have become a cornerstone in the functionality of large language models (LLMs) due to their ability to transform text data into rich, dense numerical representations that capture semantic and syntactic properties. These embedding vector da
Externí odkaz:
http://arxiv.org/abs/2411.05034
Recently, point clouds have been widely used in computer vision, whereas their collection is time-consuming and expensive. As such, point cloud datasets are the valuable intellectual property of their owners and deserve protection. To detect and prev
Externí odkaz:
http://arxiv.org/abs/2408.05500
Publikováno v:
Infectious Agents and Cancer, Vol 14, Iss 1, Pp 1-11 (2019)
Abstract Background Persistent infection with human papillomaviruses (HPVs) has been associated with cervical intraepithelial neoplasia (CIN) and cervical cancer. However, why only a fraction of HPV cases progress to cancer is still unclear. Methods
Externí odkaz:
https://doaj.org/article/d8de12f9045e434090dafd6589c45487
Multimodal Large Language Models (MLLMs) extend the capacity of LLMs to understand multimodal information comprehensively, achieving remarkable performance in many vision-centric tasks. Despite that, recent studies have shown that these models are su
Externí odkaz:
http://arxiv.org/abs/2407.21659
Autor:
Yang, Yuchen, Yao, Hongwei, Yang, Bingrun, He, Yiling, Li, Yiming, Zhang, Tianwei, Qin, Zhan, Ren, Kui
Recently, code-oriented large language models (Code LLMs) have been widely and successfully used to simplify and facilitate code programming. With these tools, developers can easily generate desired complete functional codes based on incomplete code
Externí odkaz:
http://arxiv.org/abs/2407.09164
Autor:
Ma, Binhao, Zheng, Tianhang, Hu, Hongsheng, Wang, Di, Wang, Shuo, Ba, Zhongjie, Qin, Zhan, Ren, Kui
Machine learning models trained on vast amounts of real or synthetic data often achieve outstanding predictive performance across various domains. However, this utility comes with increasing concerns about privacy, as the training data may include se
Externí odkaz:
http://arxiv.org/abs/2407.05112
The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that contradic
Externí odkaz:
http://arxiv.org/abs/2406.16333