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Very large-scale Deep Neural Networks (DNNs) have achieved remarkable successes in a large variety of computer vision tasks. However, the high computation intensity of DNNs makes it challenging to deploy these models on resource-limited systems. Some studies used low-rank approaches that approximate the filters by low-rank basis to accelerate the testing. Those works directly decomposed the pre-trained...
Despite several studies regarding the correlation between serum HBsAg titers and viral loads, the association remains uncertain. Eighty‐nine individuals were selected randomly from a Chinese cohort of 2,258 subjects infected persistently with hepatitis B virus (HBV) for cross‐sectional and longitudinal analysis. Viral loads of mutant HBV are lower than those of wild type HBV. The serum HBsAg titers...
In this paper we propose a method to estimate the InSAR interferometric phase using the correlation weight subspace projection technique. In the method the correlation weight data vector is constructed, thus the noise subspace dimension of the corresponding covariance matrix will not be affected by the coregistration error, then avoiding the trouble of calculating the noise subspace dimension before...
In this paper, an improved joint subspace projection method for synthetic aperture radar interferometry (InSAR) interferogram filtering is proposed. Benefiting from the new formulation of joint data vector, the method does not need to calculate the noise subspace dimension before estimating the InSAR interferometric phase, thus avoiding the effect on the estimation of the InSAR interferometric phase...
In this paper, a robust method for synthetic aperture radar interferometry (InSAR) interferometric phase estimation is introduced. In the method, the optimal joint data vector is determined, the generalized correlation steering vector is computed according to the data vector, and then the beamforming technique with the steering vector is used to estimate the InSAR interferometric phase. The method...
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