Zobrazeno 1 - 10
of 1 283
pro vyhledávání: '"Gan, Quan"'
The current bottleneck in continuous sign language recognition (CSLR) research lies in the fact that most publicly available datasets are limited to laboratory environments or television program recordings, resulting in a single background environmen
Externí odkaz:
http://arxiv.org/abs/2409.11960
Autor:
Wang, Minjie, Gan, Quan, Wipf, David, Cai, Zhenkun, Li, Ning, Tang, Jianheng, Zhang, Yanlin, Zhang, Zizhao, Mao, Zunyao, Song, Yakun, Wang, Yanbo, Li, Jiahang, Zhang, Han, Yang, Guang, Qin, Xiao, Lei, Chuan, Zhang, Muhan, Zhang, Weinan, Faloutsos, Christos, Zhang, Zheng
Although RDBs store vast amounts of rich, informative data spread across interconnected tables, the progress of predictive machine learning models as applied to such tasks arguably falls well behind advances in other domains such as computer vision o
Externí odkaz:
http://arxiv.org/abs/2404.18209
Changes in facial expression, head movement, body movement and gesture movement are remarkable cues in sign language recognition, and most of the current continuous sign language recognition(CSLR) research methods mainly focus on static images in vid
Externí odkaz:
http://arxiv.org/abs/2402.19118
Relational databases are extensively utilized in a variety of modern information system applications, and they always carry valuable data patterns. There are a huge number of data mining or machine learning tasks conducted on relational databases. Ho
Externí odkaz:
http://arxiv.org/abs/2312.02037
Graph neural networks (GNNs) for link prediction can loosely be divided into two broad categories. First, \emph{node-wise} architectures pre-compute individual embeddings for each node that are later combined by a simple decoder to make predictions.
Externí odkaz:
http://arxiv.org/abs/2310.09516
Autor:
Gan, Quan
Cyclic polymers are topologically interesting and envisioned as a lubricant material. However, scalable synthesis of pure cyclic polymers remains elusive. The most straightforward way is to recover a used catalyst after the synthesis of cyclic polyme
Hypergraphs are a powerful abstraction for representing higher-order interactions between entities of interest. To exploit these relationships in making downstream predictions, a variety of hypergraph neural network architectures have recently been p
Externí odkaz:
http://arxiv.org/abs/2306.09623
The goal of continuous sign language recognition(CSLR) research is to apply CSLR models as a communication tool in real life, and the real-time requirement of the models is important. In this paper, we address the model real-time problem through cros
Externí odkaz:
http://arxiv.org/abs/2303.06820
Autor:
Huang, Kezhao, Jiang, Haitian, Wang, Minjie, Xiao, Guangxuan, Wipf, David, Song, Xiang, Gan, Quan, Huang, Zengfeng, Zhai, Jidong, Zhang, Zheng
A key performance bottleneck when training graph neural network (GNN) models on large, real-world graphs is loading node features onto a GPU. Due to limited GPU memory, expensive data movement is necessary to facilitate the storage of these features
Externí odkaz:
http://arxiv.org/abs/2301.07482
Autor:
Jin, Jiarui, Wang, Yangkun, Zhang, Weinan, Gan, Quan, Song, Xiang, Yu, Yong, Zhang, Zheng, Wipf, David
Graph Neural Networks (GNNs), originally proposed for node classification, have also motivated many recent works on edge prediction (a.k.a., link prediction). However, existing methods lack elaborate design regarding the distinctions between two task
Externí odkaz:
http://arxiv.org/abs/2212.12970