With the continuous development of deep learning, face recognition field has also developed rapidly. However, with massive popularity COVID-19, masks is a problem that now about to be tackled in practice. In recognizing wearing mask, mask obscures most facial features face, resulting general model only capturing part information. Therefore, existing models are usually ineffective faces masks. T...

The images captured in the underwater scene frequently suffer from blur effects due to insufficient light and relative motion between scenes imaging system, which severely hinders visual-based exploration investigation of ocean. In this article, we propose a feature pyramid attention network (FPAN) remove restore blurry images. FPAN incorporates cascaded modules into network, enabling it learn ...

Abstract POI(point of interest) recommendation is a very necessary research field in both academic and commerce, however, predicting users’ potential points interest always faced with the problems data sparsity context semantics. Some studies have shown that graph embedding technology alleviates problem to certain extent. However, neither techniques nor unsupervised learning models can adaptive...

Research on facial recognition has recently been flourishing, which led to the introduction of many robust methods. However, since worldwide outbreak COVID-19, people have had regularly wear masks, thus making existing face methods less reliable. Although normal are nearly complete, masked (MFR)—which refers recognizing identity an individual when a mask—remains most challenging topic in this a...

In order to solve the problem of inaccurate edge segmentation and loss small buildings caused by UNet which is difficult take into account both global features local features, CSUNet proposed based on coordinate attention self-attention. The fuses in encoder, designs a Double-channel Skip Connection Transformer (DSCT) model skip connection, feature fusion module (FFM) CBAM channel fuse output c...