Zobrazeno 1 - 10
of 1 168
pro vyhledávání: '"LI Chenglin"'
Publikováno v:
能源环境保护, Vol 37, Iss 4, Pp 46-55 (2023)
Energy low-carbon transitions have become a crucial approach for countries around the world to cope with climate crisis and promote sustainable development. However, most of the existing studies have analyzed the risks and challenges of the energy lo
Externí odkaz:
https://doaj.org/article/38d0a78da3e344de9c6ce1fce3db60b2
Publikováno v:
精准医学杂志, Vol 38, Iss 3, Pp 199-204 (2023)
Objective To explore the effects of polydopamine (PDA) plus luteolin (LUT) with photothermal therapy on tumor killing by cytotoxic lymphocytes (CTL). Methods The synthesized PDA was characterized by using a scanning electron microscope (SEM) and a co
Externí odkaz:
https://doaj.org/article/e593ef3b732849d49ec27d612b99b7e6
Autor:
Li, Meng, Wang, Xiang, Nie, Liming, Li, Chenglin, Liu, Yang, Zhao, Yangyang, Xue, Lei, Said, Kabir Sulaiman
As digital interfaces become increasingly prevalent, certain manipulative design elements have emerged that may harm user interests, raising associated ethical concerns and bringing dark patterns into focus as a significant research topic. Manipulati
Externí odkaz:
http://arxiv.org/abs/2412.09147
Autor:
Xu, Wenqiang, Dai, Wenrui, Xue, Duoduo, Zheng, Ziyang, Li, Chenglin, Zou, Junni, Xiong, Hongkai
Due to limitations in acquisition equipment, noise perturbations often corrupt 3-D point clouds, hindering down-stream tasks such as surface reconstruction, rendering, and further processing. Existing 3-D point cloud denoising methods typically fail
Externí odkaz:
http://arxiv.org/abs/2411.14158
Autor:
Xu, Wenqiang, Dai, Wenrui, Xue, Duoduo, Zheng, Ziyang, Li, Chenglin, Zou, Junni, Xiong, Hongkai
Generative diffusion models have shown empirical successes in point cloud resampling, generating a denser and more uniform distribution of points from sparse or noisy 3D point clouds by progressively refining noise into structure. However, existing d
Externí odkaz:
http://arxiv.org/abs/2411.14120
Text-to-image (T2I) diffusion models, with their impressive generative capabilities, have been adopted for image editing tasks, demonstrating remarkable efficacy. However, due to attention leakage and collision between the cross-attention map of the
Externí odkaz:
http://arxiv.org/abs/2411.10232
Recent advancements in Large Video-Language Models (LVLMs) have driven the development of benchmarks designed to assess cognitive abilities in video-based tasks. However, most existing benchmarks heavily rely on web-collected videos paired with human
Externí odkaz:
http://arxiv.org/abs/2411.09105
Autor:
Li, Chenglin, Chen, Qianglong, Li, Zhi, Tao, Feng, Li, Yicheng, Chen, Hao, Yu, Fei, Zhang, Yin
Instruction tuning is a crucial technique for aligning language models with humans' actual goals in the real world. Extensive research has highlighted the quality of instruction data is essential for the success of this alignment. However, creating h
Externí odkaz:
http://arxiv.org/abs/2410.10392
Multipliers and multiply-accumulators (MACs) are critical arithmetic circuit components in the modern era. As essential components of AI accelerators, they significantly influence the area and performance of compute-intensive circuits. This paper pre
Externí odkaz:
http://arxiv.org/abs/2408.06935
Autor:
Li, Han, Li, Shaohui, Ding, Shuangrui, Dai, Wenrui, Cao, Maida, Li, Chenglin, Zou, Junni, Xiong, Hongkai
Image compression for machine and human vision (ICMH) has gained increasing attention in recent years. Existing ICMH methods are limited by high training and storage overheads due to heavy design of task-specific networks. To address this issue, in t
Externí odkaz:
http://arxiv.org/abs/2407.09853