At the prior learning stage, we first construct a large Hankel matrix from k-space data, then extract multiple structured k-space patches from the large Hankel matrix to capture the internal distribution among different patches.
Deep learning based parallel Imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI).
Decreasing magnetic resonance (MR) image acquisition times can potentially make MR examinations more accessible.
1 code implementation • • Sifeng He, Xudong Yang, Chen Jiang, Gang Liang, Wei zhang, Tan Pan, Qing Wang, Furong Xu, Chunguang Li, Jingxiong Liu, Hui Xu, Kaiming Huang, Yuan Cheng, Feng Qian, Xiaobo Zhang, Lei Yang
In this paper, we introduce VCSL (Video Copy Segment Localization), a new comprehensive segment-level annotated video copy dataset.
no code implementations • 15 Oct 2020 • Benard Nsamba, Nuno Moedas, Tiago L. Campante, Margarida S. Cunha, Antonio García Hernández, Juan C. Suárez, Mário J. P. F. G. Monteiro, João Fernandes, Chen Jiang, Babatunde Akinsanmi
Adopting 35 low-mass, solar-type stars with multi-year Kepler photometry from the asteroseismic "LEGACY" sample, we explore the systematic uncertainties on the inferred stellar parameters (i. e., radius, mass, and age) arising from the treatment of the initial helium abundance in stellar model grids .
Solar and Stellar Astrophysics
Motivated by this question and the idea in linearization framework, in this paper, we focus on the $L_2$-loss kernel SVM and propose a semismooth Newton's method based linearization and approximation approach for it.
In this paper, to model the intended concepts of manipulation, we present a vision dataset under a strictly constrained knowledge domain for both robot and human manipulations, where manipulation concepts and relations are stored by an ontology system in a taxonomic manner.
Using the framework, we present a case study where robot performs manipulation actions in a kitchen environment, bridging visual perception with contextual semantics using the generated dynamic knowledge graphs.
A human teacher can show potential objects of interest to the robot, which is able to self adapt to the teaching signal without providing manual segmentation labels.
Ranked #13 on Unsupervised Video Object Segmentation on DAVIS 2016