The issue of animal attacks is increasingly concerning for rural populations and forestry
workers. To track the movement of wild animals, surveillance cameras and drones are often …

Urban scenes segmentation based on UAV (Unmanned aerial vehicle) view is a
fundamental task for the applications of smart city such as city planning, land use monitoring …

Because deep learning has various downsides, such as complexity, expense, and the need
to wait longer for results, this creates a significant incentive and impetus to invent and adopt …

Reaction wheels are key components for the spacecraft attitude control subsystems. Faults
in reaction wheels may lead to high energy consumption, lack of spacecraft attitude control …

There are multiple uses for single-channel images, such as infrared imagery, depth maps,
and others. To automatically classify objects in such images, an algorithm suited for single …

Land cover classification is a vital task in remote sensing to emerging demands in global
and echo-friendly environmental applications. This type of analysis will empower with …

Land use and land cover (LULC) classification are one of the important tasks to monitor the
various land cover resources of the earth. In this research work, we have proposed a novel …

As farmland being the foundation of national agribusiness, it is of paramount significance to
obtain data more efficiently about the distribution of farmland for further agricultural resource …

In this paper, physics informed neural networks are used for numerical approximation of
partial differential equations. The data which is used in the process is generated by Latin …

The aim of the study is to eliminate the electricity loss of individual customers and to
overcome the economic crisis. A novel Linear Support Vector Machine (SVM) algorithm is …