Zobrazeno 1 - 10
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pro vyhledávání: '"Yen, AS"'
One common belief is that with complex models and pre-training on large-scale datasets, transformer-based methods for referring expression comprehension (REC) perform much better than existing graph-based methods. We observe that since most graph-bas
Externí odkaz:
http://arxiv.org/abs/2409.03385
Autor:
Liu, Chen-Yu, Chen, Samuel Yen-Chi
In this work, we introduce the Federated Quantum-Train (QT) framework, which integrates the QT model into federated learning to leverage quantum computing for distributed learning systems. Quantum client nodes employ Quantum Neural Networks (QNNs) an
Externí odkaz:
http://arxiv.org/abs/2409.02763
Consider the problems of computing the Augustin information and a R\'{e}nyi information measure of statistical independence, previously explored by Lapidoth and Pfister (\textit{IEEE Information Theory Workshop}, 2018) and Tomamichel and Hayashi (\te
Externí odkaz:
http://arxiv.org/abs/2409.02640
The estimated Glomerular Filtration Rate (eGFR) is an essential indicator of kidney function in clinical practice. Although traditional equations and Machine Learning (ML) models using clinical and laboratory data can estimate eGFR, accurately predic
Externí odkaz:
http://arxiv.org/abs/2409.02530
In the context of 5G platoon communications, the Platoon Leader Vehicle (PLV) employs groupcasting to transmit control messages to Platoon Member Vehicles (PMVs). Due to the restricted transmission power for groupcasting, it may need to pick one PMV
Externí odkaz:
http://arxiv.org/abs/2409.00719
Autor:
Huang, Hsiang-Wei, Sun, Jiacheng, Yang, Cheng-Yen, Jiang, Zhongyu, Huang, Li-Yu, Hwang, Jenq-Neng, Yeh, Yu-Ching
Assessing gross motor development in toddlers is crucial for understanding their physical development and identifying potential developmental delays or disorders. However, existing datasets for action recognition primarily focus on adults, lacking th
Externí odkaz:
http://arxiv.org/abs/2409.00349
Autor:
Ouyang, Shuyi, Zhang, Jinyang, Lin, Xiangye, Wang, Xilai, Chen, Qingqing, Chen, Yen-Wei, Lin, Lanfen
Conventional medical image segmentation methods have been found inadequate in facilitating physicians with the identification of specific lesions for diagnosis and treatment. Given the utility of text as an instructional format, we introduce a novel
Externí odkaz:
http://arxiv.org/abs/2408.17347
Autor:
Gu, Xinyang, Wang, Yen-Jen, Zhu, Xiang, Shi, Chengming, Guo, Yanjiang, Liu, Yichen, Chen, Jianyu
Humanoid robots, with their human-like skeletal structure, are especially suited for tasks in human-centric environments. However, this structure is accompanied by additional challenges in locomotion controller design, especially in complex real-worl
Externí odkaz:
http://arxiv.org/abs/2408.14472
Understanding people's social interactions in complex real-world scenarios often relies on intricate mental reasoning. To truly understand how and why people interact with one another, we must infer the underlying mental states that give rise to the
Externí odkaz:
http://arxiv.org/abs/2408.12574
Offline reinforcement learning (RL) learns policies from a fixed dataset, but often requires large amounts of data. The challenge arises when labeled datasets are expensive, especially when rewards have to be provided by human labelers for large data
Externí odkaz:
http://arxiv.org/abs/2408.12307