In recent years, kernel methods are widespread in tasks of similarity
me...
Imaging and perception in photon-limited scenarios is necessary for vari...
Graph matching can be formalized as a combinatorial optimization problem...
Federated learning (FL) enables the building of robust and generalizable...
Under low-light environment, handheld photography suffers from severe ca...
Quantum machine learning is a fast emerging field that aims to tackle ma...
Graph Neural Networks (GNNs) are recently proposed neural network struct...
Controlling a non-statically bipedal robot is challenging due to the com...
Semantic segmentation of building facade is significant in various
appli...
Micro-Expression Recognition has become challenging, as it is extremely
...
Although deep convolutional neural networks (DCNNs) have achieved signif...
In this work, we develop a novel framework to measure the similarity bet...
Feature selection can efficiently identify the most informative features...
Recently sparse representation has gained great success in face image
su...