Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …

Advanced Hyperspectral image sensors can capture high-resolution land cover images.
Many supervised Machine learning (ML) and Deep learning (DL) algorithms succeeded in …

Graph is a widely applied technique to characterize the relationship among data. Due to the
excellent ability to handle nonlinear data and extract the useful information contained in …

Foreign species can deteriorate the environment and the economy of a country. To
automatically monitor biosecurity threats at country borders, this paper investigates compact …

Recently, singular spectrum analysis (SSA) and two-dimensional SSA (2D-SSA) have been
utilized to successfully extract features from hyperspectral images (HSIs) in the spectral and …

Cracks in civil infrastructures are an important sign of structural degradation and may
indicate the inception of catastrophic failure. Existing image-based crack detection …

Hyperspectral images consist of rich spectral information and spatial structure information
that can be fully employed to implement the ground objects classification effectively. Due to …

Over the long-term monitoring process, the collected structural health monitoring (SHM) data
tend to be voluminous, redundant, but relevant. Although these data are in high-dimensional …

Over the past few years, deep learning (DL) has been achieving state-of-theart performance
on various human tasks such as speech generation, language translation, image …