Zobrazeno 1 - 10
of 3 131
pro vyhledávání: '"Zhang , Yuhong"'
Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from the same distribution, but struggle to generalize well in the face of distribution shifts. To address this issue, existing mainstreaming graph rationaliz
Externí odkaz:
http://arxiv.org/abs/2412.12880
Autor:
Ren, Tianhe, Chen, Yihao, Jiang, Qing, Zeng, Zhaoyang, Xiong, Yuda, Liu, Wenlong, Ma, Zhengyu, Shen, Junyi, Gao, Yuan, Jiang, Xiaoke, Chen, Xingyu, Song, Zhuheng, Zhang, Yuhong, Huang, Hongjie, Gao, Han, Liu, Shilong, Zhang, Hao, Li, Feng, Yu, Kent, Zhang, Lei
In this paper, we introduce DINO-X, which is a unified object-centric vision model developed by IDEA Research with the best open-world object detection performance to date. DINO-X employs the same Transformer-based encoder-decoder architecture as Gro
Externí odkaz:
http://arxiv.org/abs/2411.14347
Realistic image restoration is a crucial task in computer vision, and the use of diffusion-based models for image restoration has garnered significant attention due to their ability to produce realistic results. However, the quality of the generated
Externí odkaz:
http://arxiv.org/abs/2407.03635
Autor:
Zhang, Yuhong, Zhang, Hengsheng, Chai, Xinning, Cheng, Zhengxue, Xie, Rong, Song, Li, Zhang, Wenjun
Image restoration is a classic low-level problem aimed at recovering high-quality images from low-quality images with various degradations such as blur, noise, rain, haze, etc. However, due to the inherent complexity and non-uniqueness of degradation
Externí odkaz:
http://arxiv.org/abs/2407.03636
Autor:
Liao, Yuan, Zhang, Yuhong, Wang, Shenghuan, Zhang, Xiruo, Zhang, Yiling, Chen, Wei, Gu, Yuzhe, Huang, Liya
Recent advances in non-invasive EEG technology have broadened its application in emotion recognition, yielding a multitude of related datasets. Yet, deep learning models struggle to generalize across these datasets due to variations in acquisition eq
Externí odkaz:
http://arxiv.org/abs/2406.08081
Colorizing grayscale images offers an engaging visual experience. Existing automatic colorization methods often fail to generate satisfactory results due to incorrect semantic colors and unsaturated colors. In this work, we propose an automatic color
Externí odkaz:
http://arxiv.org/abs/2404.16678
The global public health landscape is perpetually challenged by the looming threat of infectious diseases. Central to addressing this concern is the imperative to prevent and manage disease transmission during pandemics, particularly in unique settin
Externí odkaz:
http://arxiv.org/abs/2404.11759
Reading comprehension, a fundamental cognitive ability essential for knowledge acquisition, is a complex skill, with a notable number of learners lacking proficiency in this domain. This study introduces innovative tasks for Brain-Computer Interface
Externí odkaz:
http://arxiv.org/abs/2401.15681
Autor:
Zhang, Yuhong, Li, Qin, Nahata, Sujal, Jamal, Tasnia, Cheng, Shih-kuen, Cauwenberghs, Gert, Jung, Tzyy-Ping
With the recent proliferation of large language models (LLMs), such as Generative Pre-trained Transformers (GPT), there has been a significant shift in exploring human and machine comprehension of semantic language meaning. This shift calls for inter
Externí odkaz:
http://arxiv.org/abs/2309.15714
In the field of intelligent education, knowledge tracing (KT) has attracted increasing attention, which estimates and traces students' mastery of knowledge concepts to provide high-quality education. In KT, there are natural graph structures among qu
Externí odkaz:
http://arxiv.org/abs/2210.15470