Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Yang Junhuan"'
Ultrasound computed tomography (USCT) is a promising technique that achieves superior medical imaging reconstruction resolution by fully leveraging waveform information, outperforming conventional ultrasound methods. Despite its advantages, high-qual
Externí odkaz:
http://arxiv.org/abs/2407.14564
Autor:
Sheng, Yi, Yang, Junhuan, Li, Jinyang, Alaina, James, Xu, Xiaowei, Shi, Yiyu, Hu, Jingtong, Jiang, Weiwen, Yang, Lei
As Artificial Intelligence (AI) increasingly integrates into our daily lives, fairness has emerged as a critical concern, particularly in medical AI, where datasets often reflect inherent biases due to social factors like the underrepresentation of m
Externí odkaz:
http://arxiv.org/abs/2407.13896
Full-waveform inversion (FWI) plays a vital role in geoscience to explore the subsurface. It utilizes the seismic wave to image the subsurface velocity map. As the machine learning (ML) technique evolves, the data-driven approaches using ML for FWI t
Externí odkaz:
http://arxiv.org/abs/2401.03131
Model fairness (a.k.a., bias) has become one of the most critical problems in a wide range of AI applications. An unfair model in autonomous driving may cause a traffic accident if corner cases (e.g., extreme weather) cannot be fairly regarded; or it
Externí odkaz:
http://arxiv.org/abs/2308.13730
Along with the breakthrough of convolutional neural networks, learning-based segmentation has emerged in many research works. Most of them are based on supervised learning, requiring plenty of annotated data; however, to support segmentation, a label
Externí odkaz:
http://arxiv.org/abs/2303.12753
Autor:
Sheng, Yi, Yang, Junhuan, Wu, Yawen, Mao, Kevin, Shi, Yiyu, Hu, Jingtong, Jiang, Weiwen, Yang, Lei
Along with the progress of AI democratization, neural networks are being deployed more frequently in edge devices for a wide range of applications. Fairness concerns gradually emerge in many applications, such as face recognition and mobile medical.
Externí odkaz:
http://arxiv.org/abs/2202.11317
Autor:
Yang, Junhuan, Sheng, Yi, Zhang, Sizhe, Wang, Ruixuan, Foreman, Kenneth, Paige, Mikell, Jiao, Xun, Jiang, Weiwen, Yang, Lei
This paper represents the first effort to explore an automated architecture search for hyperdimensional computing (HDC), a type of brain-inspired neural network. Currently, HDC design is largely carried out in an application-specific ad-hoc manner, w
Externí odkaz:
http://arxiv.org/abs/2202.05827
Autor:
Li, Bingbing, Peng, Hongwu, Sainju, Rajat, Yang, Junhuan, Yang, Lei, Liang, Yueying, Jiang, Weiwen, Wang, Binghui, Liu, Hang, Ding, Caiwen
In this paper, we propose a novel gender bias detection method by utilizing attention map for transformer-based models. We 1) give an intuitive gender bias judgement method by comparing the different relation degree between the genders and the occupa
Externí odkaz:
http://arxiv.org/abs/2110.15733
Autor:
Peng, Hongwu, Chen, Shiyang, Wang, Zhepeng, Yang, Junhuan, Weitze, Scott A., Geng, Tong, Li, Ang, Bi, Jinbo, Song, Minghu, Jiang, Weiwen, Liu, Hang, Ding, Caiwen
Molecular similarity search has been widely used in drug discovery to identify structurally similar compounds from large molecular databases rapidly. With the increasing size of chemical libraries, there is growing interest in the efficient accelerat
Externí odkaz:
http://arxiv.org/abs/2109.06355
Autor:
Liang, Zhiding, Wang, Zhepeng, Yang, Junhuan, Yang, Lei, Xiong, Jinjun, Shi, Yiyu, Jiang, Weiwen
In the noisy intermediate-scale quantum (NISQ) era, one of the key questions is how to deal with the high noise level existing in physical quantum bits (qubits). Quantum error correction is promising but requires an extensive number (e.g., over 1,000
Externí odkaz:
http://arxiv.org/abs/2109.03430