Graph-based classification algorithms have gained increasing attention in semi-supervised
classification. Nevertheless, the graph cannot fully represent the inherent spatial distribution …

Most traditional approaches classify hyperspectral image (HSI) pixels relying only on the
spectral values of the input channels. However, the spatial context around a pixel is also very …

The supervised deep networks have shown great potential in improving the classification
performance. However, training these supervised deep networks is very challenging for …

Registration for multisensor or multimodal image pairs with a large degree of distortions is a
fundamental task for many remote sensing applications. To achieve accurate and low-cost …

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replicates throughout
human airways. The polarized human airway epithelium (HAE) cultured at an airway-liquid …

Androgen receptor (AR) splice variants (ARVs) are implicated in development of castration-resistant
prostate cancer (CRPC). Upregulation of ARVs often correlates with persistent AR …

Local invariant features from computer vision community have recently been widely applied
to the matching of remote sensing images. However, these features are mainly designed to …

Remote sensing (RS) image classification has attracted much attention recently and is widely
used in various fields. Different to natural images, the RS image scenes consist of complex …

Aim Ankyloglossia is a common congenital malformation characterized by a short, thick, or
tight tongue frenulum, and its effect on speech articulation remains controversial. This study …

Variants of deep networks have been widely used for hyperspectral image (HSI)-classification
tasks. Among them, in recent years, recurrent neural networks (RNNs) have attracted …