This paper reviews the state-of-the-art representation-based classification and detection
approaches for hyperspectral remote sensing imagery, including sparse representation …

Low-light is an inescapable element of our daily surroundings that greatly affects the
efficiency of our vision. Research works on low-light imagery have seen a steady growth …

Rice lodging not only causes difficulty in harvest operations, but also drastically reduces
yield. Rice lodging assessment contributes greatly to rice plantation and crop field …

Multispectral pedestrian detection is an important functionality in various computer vision
applications such as robot sensing, security surveillance, and autonomous driving. In this …

Object detection traditionally requires sliding-window classifier in modern deep learning
based approaches. However, both of these approaches requires tedious configurations in …

Driven by the prominent thermal signature of humans and following the growing availability
of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on …

Most of the commercial nighttime pedestrian detection (PD) methods reported previously
utilized the histogram of oriented gradient (HOG) or the local binary pattern (LBP) as the …

In this paper, we propose a convolutional neural network for thermal image enhancement by
incorporating the brightness domain with a residual-learning technique, which improves the …

Keemun black tea is classified into 7 grades according to the difference in its quality. The
appearance and flavour are crucial indicators of its quality. This research demonstrates a …

With the development of intelligent surveillance systems, human behavior recognition has
been extensively researched. Most of the previous methods recognized human behavior …