Zobrazeno 1 - 10
of 877
pro vyhledávání: '"Zhou Yingjie"'
Autor:
Zhou Yingjie, Li Lixun
Publikováno v:
Redai dili, Vol 43, Iss 4, Pp 769-782 (2023)
Technological innovation is considered an important source of national economic development, but existing studies have found that there are few independent research and development (R&D) activities in Chinese enterprises, and the achievement transfor
Externí odkaz:
https://doaj.org/article/44e0d04aa4af4b3b94c74e97ff0aac38
Publikováno v:
Nanophotonics, Vol 11, Iss 19, Pp 4455-4463 (2022)
Planar optical elements have attracted widespread attentions because of their precise light modulation. Liquid crystals (LCs) are well known for their applications in the current displaying field, and show great potential in planar optical elements w
Externí odkaz:
https://doaj.org/article/5e60ffee4a654dceb32cd0f8ab22130f
Autor:
Zhou, Yingjie, Zhang, Zicheng, Cao, Jiezhang, Jia, Jun, Jiang, Yanwei, Wen, Farong, Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao
Artificial Intelligence (AI) has demonstrated significant capabilities in various fields, and in areas such as human-computer interaction (HCI), embodied intelligence, and the design and animation of virtual digital humans, both practitioners and use
Externí odkaz:
http://arxiv.org/abs/2411.11235
This paper presents a large-scale parallel solver, specifically designed to tackle the challenges of solving high-dimensional and high-contrast linear systems in heat transfer topology optimization. The solver incorporates an interpolation technique
Externí odkaz:
http://arxiv.org/abs/2410.06850
Multigrid preconditioners are one of the most powerful techniques for solving large sparse linear systems. In this research, we address Darcy flow problems with random permeability using the conjugate gradient method, enhanced by a two-grid precondit
Externí odkaz:
http://arxiv.org/abs/2410.06832
Autor:
Zhang, Zicheng, Jia, Ziheng, Wu, Haoning, Li, Chunyi, Chen, Zijian, Zhou, Yingjie, Sun, Wei, Liu, Xiaohong, Min, Xiongkuo, Lin, Weisi, Zhai, Guangtao
With the rising interest in research on Large Multi-modal Models (LMMs) for video understanding, many studies have emphasized general video comprehension capabilities, neglecting the systematic exploration into video quality understanding. To address
Externí odkaz:
http://arxiv.org/abs/2409.20063
Autor:
Zhou, Yingjie, Zhang, Zicheng, Wen, Farong, Jia, Jun, Jiang, Yanwei, Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao
Although 3D generated content (3DGC) offers advantages in reducing production costs and accelerating design timelines, its quality often falls short when compared to 3D professionally generated content. Common quality issues frequently affect 3DGC, h
Externí odkaz:
http://arxiv.org/abs/2409.07236
Quality assessment, which evaluates the visual quality level of multimedia experiences, has garnered significant attention from researchers and has evolved substantially through dedicated efforts. Before the advent of large models, quality assessment
Externí odkaz:
http://arxiv.org/abs/2409.00031
Autor:
Du, Wenjie, Wang, Jun, Qian, Linglong, Yang, Yiyuan, Ibrahim, Zina, Liu, Fanxing, Wang, Zepu, Liu, Haoxin, Zhao, Zhiyuan, Zhou, Yingjie, Wang, Wenjia, Ding, Kaize, Liang, Yuxuan, Prakash, B. Aditya, Wen, Qingsong
Effective imputation is a crucial preprocessing step for time series analysis. Despite the development of numerous deep learning algorithms for time series imputation, the community lacks standardized and comprehensive benchmark platforms to effectiv
Externí odkaz:
http://arxiv.org/abs/2406.12747
Autor:
Zhang, Zicheng, Wu, Haoning, Li, Chunyi, Zhou, Yingjie, Sun, Wei, Min, Xiongkuo, Chen, Zijian, Liu, Xiaohong, Lin, Weisi, Zhai, Guangtao
How to accurately and efficiently assess AI-generated images (AIGIs) remains a critical challenge for generative models. Given the high costs and extensive time commitments required for user studies, many researchers have turned towards employing lar
Externí odkaz:
http://arxiv.org/abs/2406.03070