Zobrazeno 1 - 10
of 1 569
pro vyhledávání: '"Wu, JiaQi"'
Autor:
Wu, Jiaqi, Zhang, Shihao, Chen, Simin, Wang, Lixu, Wang, Zehua, Chen, Wei, He, Fangyuan, Tian, Zijian, Yu, F. Richard, Leung, Victor C. M.
Edge computing has emerged as a key paradigm for deploying deep learning-based object detection in time-sensitive scenarios. However, existing edge detection methods face challenges: 1) difficulty balancing detection precision with lightweight models
Externí odkaz:
http://arxiv.org/abs/2412.18230
Autor:
Wu, Jiaqi, Chen, Simin, Yang, Yuzhe, Li, Yijiang, Hou, Shiyue, Jing, Rui, Wang, Zehua, Chen, Wei, Tian, Zijian
In recent years, large language models (LLMs) have significantly advanced the field of natural language processing (NLP). By fine-tuning LLMs with data from specific scenarios, these foundation models can better adapt to various downstream tasks. How
Externí odkaz:
http://arxiv.org/abs/2411.00985
Benefiting from improved stability due to stronger interlayer van der Waals interactions, few-layer fullerene networks are experimentally more accessible compared to monolayer polymeric C$_{60}$. However, there is a lack of systematic theoretical stu
Externí odkaz:
http://arxiv.org/abs/2411.00099
Autor:
Wu, Jiaqi, Chen, Simin, Wang, Zehua, Chen, Wei, Tian, Zijian, Yu, F. Richard, Leung, Victor C. M.
As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this by shifting data analysis to the edge. However, limited computational p
Externí odkaz:
http://arxiv.org/abs/2411.00838
Publikováno v:
J. Am. Chem. Soc. (2024)
The assembly of molecules to form covalent networks can create varied lattice structures with distinct physical and chemical properties from conventional atomic lattices. Using the smallest stable [5,6]fullerene units as building blocks, various 2D C
Externí odkaz:
http://arxiv.org/abs/2409.15421
Deep learning models generating structural brain MRIs have the potential to significantly accelerate discovery of neuroscience studies. However, their use has been limited in part by the way their quality is evaluated. Most evaluations of generative
Externí odkaz:
http://arxiv.org/abs/2409.08463
In computer vision, traditional ensemble learning methods exhibit either a low training efficiency or the limited performance to enhance the reliability of deep neural networks. In this paper, we propose a lightweight, loss-function-free, and archite
Externí odkaz:
http://arxiv.org/abs/2408.04150
Orbital degrees of freedom play an important role for understanding the emergence of unconventional quantum phases. Ultracold atomic gases in optical lattices provide a wonderful platform to simulate orbital physics. In this work, we consider spinles
Externí odkaz:
http://arxiv.org/abs/2407.00932
Autor:
Wu, Jiaqi
How to bridge generative procedural art and visual generative artificial intelligence (AI) for visual content creation is an under-explored topic. On the one hand, there are many cases where creative programmers can make use of generative AI, includi
Externí odkaz:
http://arxiv.org/abs/2406.05508
Crack detection has become an indispensable, interesting yet challenging task in the computer vision community. Specially, pavement cracks have a highly complex spatial structure, a low contrasting background and a weak spatial continuity, posing a s
Externí odkaz:
http://arxiv.org/abs/2404.12702