Results 41 to 50 of about 1,409,223 (260)

Analysis of a Simulated Optical GSO Survey Observation for the Effective Maintenance of the Catalogued Satellites and the Orbit Determination Strategy [PDF]

Journal of Astronomy and Space Sciences, 2015
A strategy is needed for a regional survey of geosynchronous orbits (GSOs) to monitor known space objects and detect uncataloged space objects. On the basis of the Inter-Agency Debris Committee’s recommendation regarding the protected region of ...
Jin Choi, Jung Hyun Jo, Hong-Suh Yim, Young-Jun Choi, Ju-Young Son, Sun-youp Park, Young-Ho Bae, Dong-Goo Roh, Sungki Cho   +8 more
doaj   +1 more source

Robust Recovery of Corrupted Image Data Based on $L_{1-2}$ Metric

IEEE Access, 2018
For removing noises and recovering intrinsic structure from corrupted image data, a classic modeling approach is based on sparsity assumption. In traditionally, the sparsity is measured by L1-norm.
Fanlong Zhang, Guowei Yang, Zhangjing Yang, Minghua Wan   +3 more
doaj   +1 more source

Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Third-order tensors have been widely used in hyperspectral remote sensing because of their ability to maintain the 3-D structure of hyperspectral images.
Pan Zheng, Hongjun Su, Qian Du
doaj   +1 more source

Optimally Sparse Frames [PDF]

, 2011
Frames have established themselves as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions.
Casazza, Peter G., Heinecke, Andreas, Krahmer, Felix, Kutyniok, Gitta   +3 more
core   +1 more source

Sparse linear representation [PDF]

2009 IEEE International Symposium on Information Theory, 2009
5 pages, to appear in proc.
Jeong, Halyun, Kim, Young-Han
openaire   +2 more sources

Tomographic SAR Imaging Method Based on Sparse and Low-rank Structures

Leida xuebao, 2022
This paper proposes a three-dimensional tomographic SAR imaging method based on a combined sparse and low-rank structures. The traditional Compressed Sensing (CS) based tomographic SAR imaging methods only utilize the sparse representation and ...
Yao ZHAO, Juncong XU, Xiangyin QUAN, Li CUI, Zhe ZHANG   +4 more
doaj   +1 more source

Sparse choice models [PDF]

2012 46th Annual Conference on Information Sciences and Systems (CISS), 2012
Choice models, which capture popular preferences over objects of interest, play a key role in making decisions whose eventual outcome is impacted by human choice behavior. In most scenarios, the choice model, which can effectively be viewed as a distribution over permutations, must be learned from observed data.
Farias, Vivek F., Jagabathula, Srikanth, Shah, Devavrat   +2 more
openaire   +4 more sources

PCGen: A Fully Parallelizable Point Cloud Generative Model

Sensors
Generative models have the potential to revolutionize 3D extended reality. A primary obstacle is that augmented and virtual reality need real-time computing.
Nicolas Vercheval, Remco Royen, Adrian Munteanu, Aleksandra Pižurica   +3 more
doaj   +1 more source

A survey of sparse representation: algorithms and applications

, 2015
Sparse representation has attracted much attention from researchers in fields of signal processing, image processing, computer vision and pattern recognition.
Li, Xuelong, Xu, Yong, Yang, Jian, Zhang, David, Zhang, Zheng   +4 more
core   +3 more sources

Multilevel Quasi-Interpolation on Chebyshev Sparse Grids

Computation
This paper investigates the potential of utilising multilevel quasi-interpolation techniques on Chebyshev sparse grids for complex numerical computations.
Faisal Alsharif
doaj   +1 more source