no code implementations • 4 Oct 2023 • Chengkang Shen, Hao Zhu, You Zhou, Yu Liu, Si Yi, Lili Dong, Weipeng Zhao, David J. Brady, Xun Cao, Zhan Ma, Yi Lin
Myocardial motion tracking stands as an essential clinical tool in the prevention and detection of Cardiovascular Diseases (CVDs), the foremost cause of death globally.
no code implementations • 8 Jan 2023 • Daoyu Li, Hanwen Xu, Miao Cao, Xin Yuan, David J. Brady, Liheng Bian
However, the computational cost has inhibited NLR from seeking global structural similarity, which consequentially keeps it trapped in the tradeoff between accuracy and efficiency and prevents it from high-dimensional large-scale tasks.
1 code implementation • 23 Mar 2022 • Qian Huang, Zhipeng Dong, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
Coherent illumination reflected by a remote target may be secondarily scattered by intermediate objects or materials.
1 code implementation • 5 Nov 2021 • Chengyu Wang, Minghao Hu, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
We use convolutional neural networks to recover images optically down-sampled by $6. 7\times$ using coherent aperture synthesis over a 16 camera array.
no code implementations • 18 Sep 2021 • Jinli Suo, Weihang Zhang, Jin Gong, Xin Yuan, David J. Brady, Qionghai Dai
Signal capture stands in the forefront to perceive and understand the environment and thus imaging plays the pivotal role in mobile vision.
no code implementations • 7 Mar 2021 • Xin Yuan, David J. Brady, Aggelos K. Katsaggelos
Via novel optical designs, the 2D detector samples the HD data in a {\em compressive} manner; following this, algorithms are employed to reconstruct the desired HD data-cube.
1 code implementation • 9 Dec 2020 • David J. Brady, Timothy J. Schulz, Chengyu Wang
Phase-sensitive sensor planes using such devices could eliminate the need both for lenses and reference signals, creating a path to large aperture diffraction limited laser imaging.
no code implementations • CVPR 2020 • Xueyang Wang, Xiya Zhang, Yinheng Zhu, Yuchen Guo, Xiaoyun Yuan, Liuyu Xiang, Zerun Wang, Guiguang Ding, David J. Brady, Qionghai Dai, Lu Fang
We believe PANDA will contribute to the community of artificial intelligence and praxeology by understanding human behaviors and interactions in large-scale real-world scenes.
3 code implementations • 20 Jul 2018 • Yang Liu, Xin Yuan, Jinli Suo, David J. Brady, Qionghai Dai
We further investigate the special structure of the sampling process in SCI to tackle the computational workload and memory issues in SCI reconstruction.
no code implementations • 29 Jan 2016 • Ikenna Odinaka, Joseph A. O'Sullivan, David G. Politte, Kenneth P. MacCabe, Yan Kaganovsky, Joel A. Greenberg, Manu Lakshmanan, Kalyani Krishnamurthy, Anuj Kapadia, Lawrence Carin, David J. Brady
In x-ray coherent scatter tomography, tomographic measurements of the forward scatter distribution are used to infer scatter densities within a volume.
no code implementations • 29 Jan 2016 • Ikenna Odinaka, Yan Kaganovsky, Joel A. Greenberg, Mehadi Hassan, David G. Politte, Joseph A. O'Sullivan, Lawrence Carin, David J. Brady
We pursue an optimization transfer approach where convex decompositions are used to lift the problem such that all hyper-voxels can be updated in parallel and in closed-form.
1 code implementation • 29 Dec 2014 • Yan Kaganovsky, Shaobo Han, Soysal Degirmenci, David G. Politte, David J. Brady, Joseph A. O'Sullivan, Lawrence Carin
We propose a globally convergent alternating minimization (AM) algorithm for image reconstruction in transmission tomography, which extends automatic relevance determination (ARD) to Poisson noise models with Beer's law.
no code implementations • 12 Oct 2014 • Xin Yuan, Patrick Llull, David J. Brady, Lawrence Carin
A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system.
no code implementations • CVPR 2014 • Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady, Lawrence Carin
A simple and inexpensive (low-power and low-bandwidth) modification is made to a conventional off-the-shelf color video camera, from which we recover {multiple} color frames for each of the original measured frames, and each of the recovered frames can be focused at a different depth.
no code implementations • 14 Feb 2013 • Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin
This paper introduces the concept of adaptive temporal compressive sensing (CS) for video.