Zobrazeno 1 - 10
of 105
pro vyhledávání: '"LIU Zimo"'
Autor:
LIU Zimo, TANG Bin, HUANG Zhihong, WANG Chuanbing, ZHANG Qilin, CHENG Song, CHEN Xuzhi, SUN Changhong
Publikováno v:
Meikuang Anquan, Vol 53, Iss 2, Pp 74-79 (2022)
The pipe jacking method has high construction safety, fast tunneling speed, convenient and flexible construction. However, if it is used in deep strata of coal mines, it will face challenges such as high ground stress and complex geological condition
Externí odkaz:
https://doaj.org/article/17a150a31e0a44c6b615c86caf9681a5
Publikováno v:
Meikuang Anquan, Vol 53, Iss 2, Pp 104-111 (2022)
In order to study the failure mechanism of surrounding rock of TBM assembly chamber in deep coal mine and optimize its support scheme, taking the construction of TBM assembly chamber in Zhangji Coal Mine as the engineering background, the numerical m
Externí odkaz:
https://doaj.org/article/7d306e0f6e60486890af3299d34faf45
Autor:
Li, Zhuo, Luo, Mingshuang, Hou, Ruibing, Zhao, Xin, Liu, Hao, Chang, Hong, Liu, Zimo, Li, Chen
Human motion generation plays a vital role in applications such as digital humans and humanoid robot control. However, most existing approaches disregard physics constraints, leading to the frequent production of physically implausible motions with p
Externí odkaz:
http://arxiv.org/abs/2411.14951
Autor:
Luo, Mingshuang, Hou, Ruibing, Li, Zhuo, Chang, Hong, Liu, Zimo, Wang, Yaowei, Shan, Shiguang
This paper presents M$^3$GPT, an advanced $\textbf{M}$ultimodal, $\textbf{M}$ultitask framework for $\textbf{M}$otion comprehension and generation. M$^3$GPT operates on three fundamental principles. The first focuses on creating a unified representat
Externí odkaz:
http://arxiv.org/abs/2405.16273
Pre-trained vision-language models learn massive data to model unified representations of images and natural languages, which can be widely applied to downstream machine learning tasks. In addition to zero-shot inference, in order to better adapt pre
Externí odkaz:
http://arxiv.org/abs/2406.18550
Displaying high-quality images on edge devices, such as augmented reality devices, is essential for enhancing the user experience. However, these devices often face power consumption and computing resource limitations, making it challenging to apply
Externí odkaz:
http://arxiv.org/abs/2401.12587
Text-based Person Retrieval (TPR) aims to retrieve the target person images given a textual query. The primary challenge lies in bridging the substantial gap between vision and language modalities, especially when dealing with limited large-scale dat
Externí odkaz:
http://arxiv.org/abs/2309.09496
Lifelong person re-identification (LReID) is in significant demand for real-world development as a large amount of ReID data is captured from diverse locations over time and cannot be accessed at once inherently. However, a key challenge for LReID is
Externí odkaz:
http://arxiv.org/abs/2211.16201
Partial label learning (PLL) learns from training examples each associated with multiple candidate labels, among which only one is valid. In recent years, benefiting from the strong capability of dealing with ambiguous supervision and the impetus of
Externí odkaz:
http://arxiv.org/abs/2210.11194
Autor:
Liu, Zimo a, c, 1, Xie, Wenqing a, d, 1, Li, Hengzhen a, d, Liu, Xu a, d, Lu, Yao a, c, Lu, Bangbao a, d, Deng, Zhenhan b, ∗∗, Li, Yusheng a, d, ∗
Publikováno v:
In Genes & Diseases November 2024 11(6)