Zobrazeno 1 - 10
of 1 425
pro vyhledávání: '"Brady, David"'
Autor:
Shen, Chengkang, Zhu, Hao, Zhou, You, Liu, Yu, Yi, Si, Dong, Lili, Zhao, Weipeng, Brady, David J., Cao, Xun, Ma, Zhan, Lin, Yi
Publikováno v:
IEEE Transactions on Medical Imaging, June 2024
Myocardial motion tracking stands as an essential clinical tool in the prevention and detection of cardiovascular diseases (CVDs), the foremost cause of death globally. However, current techniques suffer from incomplete and inaccurate motion estimati
Externí odkaz:
http://arxiv.org/abs/2310.02792
Autor:
Wang, Xiao, Redding, Brandon, Karl, Nicholas, Long, Christopher, Zhu, Zheyuan, Pang, Shuo, Brady, David, Sarma, Raktim
Modern lens designs are capable of resolving >10 gigapixels, while advances in camera frame-rate and hyperspectral imaging have made Terapixel/s data acquisition a real possibility. The main bottlenecks preventing such high data-rate systems are powe
Externí odkaz:
http://arxiv.org/abs/2306.04554
Computational reconstruction plays a vital role in computer vision and computational photography. Most of the conventional optimization and deep learning techniques explore local information for reconstruction. Recently, nonlocal low-rank (NLR) recon
Externí odkaz:
http://arxiv.org/abs/2301.03047
Autor:
Bahcivan, Hasan, Brady, David J.
In a companion article, we discussed the radiometric sensitivity and resolution of a new passive optical sensing technique, Space-Time Projection Optical Tomography (SPOT), to detect and track sub-cm and larger space debris for Space Situational Awar
Externí odkaz:
http://arxiv.org/abs/2211.13040
We consider sampling and detection strategies for solar illuminated space debris. We argue that the lowest detectable debris cross section may be reduced by 10-100x by analysis of phase-space-pixels rather than single frame data. The phase-space-pixe
Externí odkaz:
http://arxiv.org/abs/2211.09789
We demonstrate a physics-aware transformer for feature-based data fusion from cameras with diverse resolution, color spaces, focal planes, focal lengths, and exposure. We also demonstrate a scalable solution for synthetic training data generation for
Externí odkaz:
http://arxiv.org/abs/2207.02250