Multitask learning (MTL) leverages task-relatedness to enhance performan...
Regression analysis is a key area of interest in the field of data analy...
Binary feature descriptors have been widely used in various visual
measu...
Line segment detection plays a cornerstone role in computer vision tasks...
Multi-view subspace clustering methods have employed learned
self-repres...
Detection and description of line segments lay the basis for numerous vi...
Deep neural networks have achieved great success in many data processing...
Multitask learning (MTL) can utilize the relatedness between multiple ta...
With powerful ability to exploit latent structure of self-representation...
We present a novel no-reference quality assessment metric, the image
tra...
The existing tensor networks adopt conventional matrix product for
conne...
Recently, adversarial attack methods have been developed to challenge th...
Although there are massive parameters in deep neural networks, the train...
Deep learning has been used to image compressive sensing (CS) for enhanc...
A single perturbation can pose the most natural images to be misclassifi...
Maximum consensus (MC) robust fitting is a fundamental problem in low-le...
Low rank tensor ring model is powerful for image completion which recove...
Tensor completion can estimate missing values of a high-order data from ...
Most compressive sensing (CS) reconstruction methods can be divided into...
Robust tensor principal component analysis (RTPCA) can separate the low-...
Deep learning models are known to be vulnerable to adversarial examples....
Machine learning models are vulnerable to adversarial examples. For the
...
The coupled tensor decomposition aims to reveal the latent data structur...
Robust tensor completion recoveries the low-rank and sparse parts from i...
The recently prevalent tensor train (TT) and tensor ring (TR) decomposit...
Tensor completion aims to recover a multi-dimensional array from its
inc...
Tensor completion aims to recover a multi-dimensional array from its
inc...
Sign information is the key to overcoming the inevitable saturation erro...
Image ordinal classification refers to predicting a discrete target valu...
Tensor completion recovers missing entries of multiway data. Teh missing...
Deep network pruning is an effective method to reduce the storage and
co...
Face photo synthesis from simple line drawing is a one-to-many task as s...
Tensor principal component analysis (TPCA) is a multi-linear extension o...
Many works have concentrated on visualizing and understanding the inner
...
Goal: This paper deals with the problems that some EEG signals have no g...
Compressed sensing (CS) shows that a signal having a sparse or compressi...