Contemporary deep learning multi-scale deblurring models suffer from man...
We propose a Multi-level Second-order (MlSo) few-shot learning network f...
Insider threat detection has been a challenging task over decades, exist...
Power Normalizations (PN) are useful non-linear operators which tackle
f...
The dual-pixel (DP) hardware works by splitting each pixel in half and
c...
The majority of existing few-shot learning describe image relations with...
Most existing few-shot learning methods in computer vision focus on clas...
Learning concepts from the limited number of datapoints is a challenging...
Learning new concepts from a few of samples is a standard challenge in
c...
Despite deep end-to-end learning methods have shown their superiority in...
Second- and higher-order statistics of data points have played an import...
In the problem of generalized zero-shot learning, the datapoints from un...
Power Normalizations (PN) are very useful non-linear operators in the co...
In this paper, we address an open problem of zero-shot learning. Its
pri...
In this paper, we approach an open problem of artwork identification and...