Results 1 to 10 of about 136,567 (283)
Journal of Open Research Software, 2014 Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating ...
Christian Schou Oxvig +4 more
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Compressed Sensing for Tactile Skins
, 2016 Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor elements.
Hollis, Brayden +2 more
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Blockchain-Watermarking for Compressive Sensed Images
IEEE Access, 2021 With the application of multimedia big data, the problems such as information leakage and data tampering have emerged. The security of images which is one of the most typical multimedia has become a major problem facing the large-scale open network ...
Ming Li +5 more
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Quasi-linear Compressed Sensing [PDF]
Multiscale Modeling & Simulation, 2014 Inspired by significant real-life applications, in particular, sparse phase retrieval and sparse pulsation frequency detection in Asteroseismology, we investigate a general framework for compressed sensing, where the measurements are quasi-linear.
Martin Ehler +2 more
openaire +2 more sources
Fast Compressed Sensing of 3D Radial T1 Mapping with Different Sparse and Low-Rank Models
Journal of Imaging, 2023 Knowledge of the relative performance of the well-known sparse and low-rank compressed sensing models with 3D radial quantitative magnetic resonance imaging acquisitions is limited.
Antti Paajanen +5 more
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Distributed Quantization for Compressed Sensing
, 2014 We study distributed coding of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a distributed framework for realizing optimized quantizer that enables encoding CS measurements of correlated sparse sources followed by joint ...
Chatterjee, Saikat +2 more
core +1 more source
Deterministic Construction of Compressed Sensing Matrices via Vector Spaces Over Finite Fields
IEEE Access, 2020 Compressed Sensing (CS) is a new signal processing theory under the condition that the signal is sparse or compressible. One of the central problems in compressed sensing is the construction of sensing matrices.
Xuemei Liu, Lihua Jia
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Compressive Imaging of Subwavelength Structures II. Periodic Rough Surfaces
, 2011 A compressed sensing scheme for near-field imaging of corrugations of relative sparse Fourier components is proposed. The scheme employs random sparse measurement of near field to recover the angular spectrum of the scattered field.
Albert Fannjiang +32 more
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Hamming Compressed Sensing [PDF]
, 2011 Compressed sensing (CS) and 1-bit CS cannot directly recover quantized signals and require time consuming recovery. In this paper, we introduce \textit{Hamming compressed sensing} (HCS) that directly recovers a k-bit quantized signal of dimensional $n ...
Tao, Dacheng, Zhou, Tianyi
core