Zobrazeno 1 - 10
of 99 048
pro vyhledávání: '"A, Eng"'
Existing unsupervised distillation-based methods rely on the differences between encoded and decoded features to locate abnormal regions in test images. However, the decoder trained only on normal samples still reconstructs abnormal patch features we
Externí odkaz:
http://arxiv.org/abs/2501.00346
High-fidelity speech enhancement often requires sophisticated modeling to capture intricate, multiscale patterns. Standard activation functions, while introducing nonlinearity, lack the flexibility to fully address this complexity. Kolmogorov-Arnold
Externí odkaz:
http://arxiv.org/abs/2412.17778
This paper serves as a reference and introduction to using the R package dapper. dapper encodes a sampling framework which allows exact Markov chain Monte Carlo simulation of parameters and latent variables in a statistical model given privatized dat
Externí odkaz:
http://arxiv.org/abs/2412.14503
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