Zobrazeno 1 - 10
of 26 147
pro vyhledávání: '"P. Eng."'
Autor:
Huang, Guang-Bin, Westover, M. Brandon, Tan, Eng-King, Wang, Haibo, Cui, Dongshun, Ma, Wei-Ying, Wang, Tiantong, He, Qi, Wei, Haikun, Wang, Ning, Tian, Qiyuan, Lam, Kwok-Yan, Yao, Xin, Wong, Tien Yin
Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. One fundamental critical question w
Externí odkaz:
http://arxiv.org/abs/2412.06820
Autor:
He, Haorui, Song, Yuchen, Wang, Yuancheng, Li, Haoyang, Zhang, Xueyao, Wang, Li, Huang, Gongping, Chng, Eng Siong, Wu, Zhizheng
One-shot voice conversion (VC) aims to alter the timbre of speech from a source speaker to match that of a target speaker using just a single reference speech from the target, while preserving the semantic content of the original source speech. Despi
Externí odkaz:
http://arxiv.org/abs/2411.19770
Neural audio codecs have revolutionized audio processing by enabling speech tasks to be performed on highly compressed representations. Recent work has shown that speech separation can be achieved within these compressed domains, offering faster trai
Externí odkaz:
http://arxiv.org/abs/2411.17998
Autor:
Li, Yikun, Zhang, Ting, Widyasari, Ratnadira, Tun, Yan Naing, Nguyen, Huu Hung, Bui, Tan, Irsan, Ivana Clairine, Cheng, Yiran, Lan, Xiang, Ang, Han Wei, Liauw, Frank, Weyssow, Martin, Kang, Hong Jin, Ouh, Eng Lieh, Shar, Lwin Khin, Lo, David
Accurate identification of software vulnerabilities is crucial for system integrity. Vulnerability datasets, often derived from the National Vulnerability Database (NVD) or directly from GitHub, are essential for training machine learning models to d
Externí odkaz:
http://arxiv.org/abs/2411.17274
Autor:
Jin, Yuhao, Gao, Qizhong, Zhu, Xiaohui, Yue, Yong, Lim, Eng Gee, Chen, Yuqing, Wong, Prudence, Chu, Yijie
While deep learning-based robotic grasping technology has demonstrated strong adaptability, its computational complexity has also significantly increased, making it unsuitable for scenarios with high real-time requirements. Therefore, we propose a lo
Externí odkaz:
http://arxiv.org/abs/2411.12520
Autor:
Yu, Yi, Ge, Junyu, Luo, Manlin, Seo, In Cheol, Kim, Youngmin, Eng, John J. H., Lu, Kunze, Wei, Tian-Ran, Gao, Weibo, Li, Hong, Nam, Donguk
Two-dimensional (2D) materials have emerged as promising candidates for next-generation integrated single-photon emitters (SPEs). However, significant variability in the emission energies of 2D SPEs presents a major challenge in producing identical s
Externí odkaz:
http://arxiv.org/abs/2410.17654
Publikováno v:
29th International Conference on Automation and Computing (ICAC 2024)
This paper has proposed a Digital Twin (DT) framework for real-time motion and pose control of soft robotic grippers. The developed DT is based on an industrial robot workstation, integrated with our newly proposed approach for soft gripper control,
Externí odkaz:
http://arxiv.org/abs/2410.14928
Autor:
Zhang, Yusong, Dong, Dong, Hung, Chi-tim, Heyerdahl, Leonard, Giles-Vernick, Tamara, Yeoh, Eng-kiong
Large Language Models (LLMs) have demonstrated remarkable capabilities in language understanding and generation. Advanced utilization of the knowledge embedded in LLMs for automated annotation has consistently been explored. This study proposed to de
Externí odkaz:
http://arxiv.org/abs/2410.11526
Millimeter-wave radar is promising to provide robust and accurate vital sign monitoring in an unobtrusive manner. However, the radar signal might be distorted in propagation by ambient noise or random body movement, ruining the subtle cardiac activit
Externí odkaz:
http://arxiv.org/abs/2410.08656
Autor:
Li, Siqi, Wu, Qiming, Li, Xin, Miao, Di, Hong, Chuan, Gu, Wenjun, Shang, Yuqing, Okada, Yohei, Chen, Michael Hao, Yan, Mengying, Ning, Yilin, Ong, Marcus Eng Hock, Liu, Nan
Objective: Mitigating algorithmic disparities is a critical challenge in healthcare research, where ensuring equity and fairness is paramount. While large-scale healthcare data exist across multiple institutions, cross-institutional collaborations of
Externí odkaz:
http://arxiv.org/abs/2410.17269