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An adaptive data rebalancing framework for real-time traffic risk prediction. [PDF]

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Chen S, Cui B, Chang A.
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When Randomness Helps in Undersampling

SIAM Review, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Roel Snieder, Michael B. Wakin
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An Undersampling Digital Microphone

2007 IEEE International Symposium on Circuits and Systems (ISCAS), 2007
As negative feedback in control systems is often not applicable and/or produces undesirable effects, this paper presents the analysis and simulation of a digital microphone using a sigma delta A/D converter comprising of a voltage controlled oscillator (VCO) and sampling D-FF to digitize data.
Sven Soell, Bernd Porr
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Regularization for Undersampled Ptychography

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), 2021
Ptychography becomes increasingly ill-posed when the overlap between neighboring scan points is reduced, inhibiting the object reconstruction. Here, we discuss and show reconstructions with low-overlap ratios by regularizing with priors such as Total- Variation and Structure-Tensor-Prior.
Prasan Shedligeri, Florian Schiffers, Semih Barutcu, Pablo Ruiz, Aggelos K. Katsaggelos, Oliver Cossairt   +5 more
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Unaliasing of undersampled spectra

2016 5th Mediterranean Conference on Embedded Computing (MECO), 2016
One of parts of digital signal processing is processing with undersampling. In this case, the sampling frequency is lower, than it is required by the sampling theorem. At undersampling, the spectrum of signals is distorted by an aliasing. Various ways of correction of the arising distortions are known. These ways are known under the name the unaliasing.
Vladislav A. Lesnikov, Tatiana V. Naumovich, Alexander V. Chastikov, Denis Garsh   +3 more
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Incremental Hashing with Undersampling

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019
Most of current hashing methods are proposed based on the assumption that the database is stationary. However, this assumption is not always true as the data environment is sometimes non-stationary. When new images being added to the database, data distributions of existing classes may change and new classes may also appear which result in concept ...
Xiaoxia Jiang, Wing W. Y. Ng, Xing Tian, Sam Kwong, Hui Wang 0001   +4 more
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Detecting undersampling in surface reconstruction

Proceedings of the seventeenth annual symposium on Computational geometry, 2001
Current surface reconstruction algorithms perform satisfactorily on we ll-sampled, smooth surfaces without boundaries. However, these algorithms face difficulty with undersampling. Cases of undersampling are prevalent in real data since often they sample a part of the boundary of an object, or are derived from a surface with high curvature or ...
Tamal K. Dey, Joachim Giesen
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Wiener reconstruction of undersampled imagery

Journal of the Optical Society of America A, 2009
We derive a Fourier-domain Wiener filter for the reconstruction of undersampled imagery. The filter differs from previous implementations in that it permits adjustment of the trade-offs between sharpness of the reconstruction, noise amplification, and aliasing artifact suppression.
Samuel T, Thurman, James R, Fienup
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Maritime Surveillance With Undersampled SAR

IEEE Geoscience and Remote Sensing Letters, 2017
According to the minimum antenna area constraint, synthetic aperture radar (SAR) systems require a low-pulse repetition frequency (PRF) to image the wide swaths in ocean surface monitoring scenarios. However, the low PRF that is lower than the Doppler bandwidth will cause azimuth ambiguities.
Yuying Wang, Zhimin Zhang 0001, Ning Li 0002, Feng Hong 0002, Huaitao Fan, Xiangyu Wang 0004   +5 more
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FIUS: Fixed partitioning undersampling method

Clinica Chimica Acta, 2021
In the medical field, data techniques for prediction and finding patterns of prevalent diseases are of increasing interest. Classification is one of the methods used to provide insight into predicting the future onset of type 2 diabetes of those at high risk of progression from pre-diabetes to diabetes.
Azam, Dekamin, M I M, Wahab, Aziz, Guergachi, Karim, Keshavjee   +3 more
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