Zobrazeno 1 - 10
of 17 037
pro vyhledávání: '"Chen Chi-An"'
Plane instance segmentation from RGB-D data is a crucial research topic for many downstream tasks. However, most existing deep-learning-based methods utilize only information within the RGB bands, neglecting the important role of the depth band in pl
Externí odkaz:
http://arxiv.org/abs/2410.16545
In an era where cultural preservation is increasingly intertwined with technological innovation, this study introduces a groundbreaking approach to promoting and safeguarding the rich heritage of Taiwanese Hakka culture through the development of a R
Externí odkaz:
http://arxiv.org/abs/2410.15572
Autor:
Li, Tian-Ming, Zhang, Jia-Chi, Chen, Bing-Jie, Huang, Kaixuan, Liu, Hao-Tian, Xiao, Yong-Xi, Deng, Cheng-Lin, Liang, Gui-Han, Chen, Chi-Tong, Liu, Yu, Li, Hao, Bao, Zhen-Ting, Zhao, Kui, Xu, Yueshan, Li, Li, He, Yang, Liu, Zheng-He, Yu, Yi-Han, Zhou, Si-Yun, Liu, Yan-Jun, Song, Xiaohui, Zheng, Dongning, Xiang, Zhong-Cheng, Shi, Yun-Hao, Xu, Kai, Fan, Heng
For superconducting quantum processors, stable high-fidelity two-qubit operations depend on precise flux control of the tunable coupler. However, the pulse distortion poses a significant challenge to the control precision. Current calibration methods
Externí odkaz:
http://arxiv.org/abs/2410.15041
Autor:
Wang, Ziyue, Chen, Chi, Luo, Fuwen, Dong, Yurui, Zhang, Yuanchi, Xu, Yuzhuang, Wang, Xiaolong, Li, Peng, Liu, Yang
Active perception, a crucial human capability, involves setting a goal based on the current understanding of the environment and performing actions to achieve that goal. Despite significant efforts in evaluating Multimodal Large Language Models (MLLM
Externí odkaz:
http://arxiv.org/abs/2410.04659
Autor:
Chen, Chi-Sheng
NECOMIMI (NEural-COgnitive MultImodal EEG-Informed Image Generation with Diffusion Models) introduces a novel framework for generating images directly from EEG signals using advanced diffusion models. Unlike previous works that focused solely on EEG-
Externí odkaz:
http://arxiv.org/abs/2410.00712
This study introduces a comprehensive benchmark designed to evaluate the performance of large language models (LLMs) in understanding and processing cultural knowledge, with a specific focus on Hakka culture as a case study. Leveraging Bloom's Taxono
Externí odkaz:
http://arxiv.org/abs/2409.01556
This paper introduces VoxHakka, a text-to-speech (TTS) system designed for Taiwanese Hakka, a critically under-resourced language spoken in Taiwan. Leveraging the YourTTS framework, VoxHakka achieves high naturalness and accuracy and low real-time fa
Externí odkaz:
http://arxiv.org/abs/2409.01548
Random spin systems at low temperatures are glassy and feature computational hardness in finding low-energy states. We study the random all-to-all interacting fermionic Sachdev--Ye--Kitaev (SYK) model and prove that, in contrast, (I) the low-energy s
Externí odkaz:
http://arxiv.org/abs/2408.15699
We investigate the emergence of stable subspaces in the low-temperature quantum thermal dynamics of finite spin chains. Our analysis reveals the existence of effective decoherence-free qudit subspaces, persisting for timescales exponential in $\beta$
Externí odkaz:
http://arxiv.org/abs/2408.14970
In this paper, we propose a novel framework for multimodal contrastive learning utilizing a quantum encoder to integrate EEG (electroencephalogram) and image data. This groundbreaking attempt explores the integration of quantum encoders within the tr
Externí odkaz:
http://arxiv.org/abs/2408.13919