Due to the data distribution discrepancy, fault diagnosis models, trained with labeled data in
one scene, likely fails in classifying by unlabeled data acquired from the other scenes …

With a great success of the generative model via deep neural networks, monocular depth
estimation has been actively studied by exploiting various encoder-decoder architectures …

It is significant to boost the performance of fault diagnosis of wind turbine gearboxes. In this
paper, a hybrid attention improved residual network (HA-ResNet) based method is proposed …

This paper presents a mosaic convolution-attention network (MCAN) for demosaicing
spectral mosaic images captured using multispectral filter array (MSFA) imaging sensors …

Zn vapour is easily generated on the surface by fusion welding galvanized steel sheet,
resulting in the formation of defects. The present study develops a novel method for …

Image super-resolution (SR) techniques improve various remote sensing applications by
allowing for finer spatial details than those captured by the original acquisition sensors …

In this paper, we propose a novel end-to-end model for fusing medical images
characterizing structural information, ie, IS, and images characterizing functional information …

Normalized difference vegetation index (NDVI), derived from multi-spectral (MS) images, is a
metric widely used to evaluate the growth status of vegetation in remote sensing. Existing …

Learning to generate three dimensional (3D) point clouds from a single image remains a
challenging task. Numerous approaches with encoder–decoder architectures have been …

The presence of surface defects during abrasive belt grinding has a significant impact on the
service performance of the parts, and the precise extraction of surface defect feature …