Video object detection, a basic task in the computer vision field, is rapidly evolving and
widely used. In recent years, deep learning methods have rapidly become widespread in the …

Computer vision applications based on videos often require the detection of moving objects
in their first step. Background subtraction is then applied in order to separate the background …

The excellent performance of graph convolutional networks (GCNs) on non-Euclidean data
has drawn widespread attention from the hyperspectral image classification (HSIC) …

Artificial neural networks (ANN) have attracted significant attention from researchers
because many complex problems can be solved by training them. If enough data are …

The visibility of images of outdoor road scenes will generally become degraded when
captured during inclement weather conditions. Drivers often turn on the headlights of their …

A recurrent fuzzy neural cerebellar model articulation network (RFNCMAN) fault-tolerant
control of a six-phase permanent magnet synchronous motor (PMSM) position servo drive is …

Recently emerged deep learning methods have achieved great success in single image rain
streaks removal. However, existing methods ignore an essential factor in the rain streaks …

The current shadow removal pipeline relies on the detected shadow masks, which have
limitations for penumbras and tiny shadows, and results in an excessively long pipeline. To …

Images captured during sandstorm conditions frequently feature degraded visibility and
undesirable color cast effects. In such situations, traditional visibility restoration approaches …

One-shot semantic segmentation poses the challenging task of segmenting object regions
from unseen categories with only one annotated example as guidance. Thus, how to …