Results 41 to 50 of about 337,735 (278)
Wearable Depth Camera: Monocular Depth Estimation via Sparse Optimization Under Weak Supervision
IEEE Access, 2018 Depth estimation is essential for many human-object interaction tasks. Despite its advantages, traditional depth sensors, including Kinect or depth camera, are always not wearable-friendly due to several critical drawbacks, such as over-size or over ...
Li He +4 more
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Case Study on the Fitting Method of Typical Objects
Photonics, 2021 This study proposes different fitting methods for different types of targets in the 400–900 nm wavelength range, based on convex optimization algorithms, to achieve the effect of high-precision spectral reconstruction for small space-borne spectrometers.
Liu Zhang +4 more
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Block-Sparse Recovery via Convex Optimization [PDF]
, 2012 Given a dictionary that consists of multiple blocks and a signal that lives in the range space of only a few blocks, we study the problem of finding a block-sparse representation of the signal, i.e., a representation that uses the minimum number of ...
Ehsan Elhamifar +3 more
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IEEE Access, 2020 As the backbone of many real-world complex systems, networks interact with others in nontrivial ways from time to time. It is a challenging problem to detect subgraphs that have dependencies on each other across multiple networks.
Fei Jie +4 more
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Applied Sciences, 2020 Image blurs are a major source of degradation in an imaging system. There are various blur types, such as motion blur and defocus blur, which reduce image quality significantly.
Haoyuan Yang, Xiuqin Su, Songmao Chen
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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Motor imagery-based brain-computer interfaces (MI-BCIs) features are generally extracted from a wide fixed frequency band and time window of EEG signal. The performance suffers from individual differences in corresponding time to MI tasks.
Jing Jin +4 more
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Recovery of binary sparse signals from compressed linear measurements via polynomial optimization [PDF]
, 2019 The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics.
Abuabiah, Mohammad, Fosson, Sophie M.
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Optimal $k$-Thresholding Algorithms for Sparse Optimization Problems [PDF]
SIAM Journal on Optimization, 2020 The simulations indicate that the existing hard thresholding technique independent of the residual function may cause a dramatic increase or numerical oscillation of the residual. This inherit drawback of the hard thresholding renders the traditional thresholding algorithms unstable and thus generally inefficient for solving practical sparse ...
openaire +2 more sources
Open Journal of Mathematical Optimization, 2021 The M-P (Moore–Penrose) pseudoinverse has as a key application the computation of least-squares solutions of inconsistent systems of linear equations. Irrespective of whether a given input matrix is sparse, its M-P pseudoinverse can be dense, potentially
Fampa, Marcia, Lee, Jon, Ponte, Gabriel
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Compressed sensing using sparse binary measurements: a rateless coding perspective [PDF]
, 2015 Compressed Sensing (CS) methods using sparse binary measurement matrices and iterative message-passing re- covery procedures have been recently investigated due to their low computational complexity and excellent performance.
Pizurica, Aleksandra +2 more
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