Livestock production is vital in eradicating poverty, malnutrition, and in attainment of the
Sustainable Development Goals (SDG) in develo** regions such as Africa. The livestock …

Deep learning is an effective machine learning method that in recent years has been
successfully applied to detect and monitor species population in remotely sensed data. This …

Drones are widely used for wildlife monitoring. Deep learning algorithms are key to the
success of monitoring wildlife with drones, although they face the problem of detecting small …

Accurate livestock counts are essential for effective pastureland management. High spatial
resolution remote sensing, coupled with deep learning, has shown promising results in …

Due to developments in science and technology, the field of plant protection and the
information industry have become increasingly integrated, which has resulted in the creation …

In recent times, designated grazing areas/fields or routes for livestock grazing are usually
defined. Hence, their herding activities' success relies on data extracted from aerial …

The unmanned aerial vehicle (UAV) remote sensing technology provides new opportunities
to estimate crop aboveground biomass (AGB). However, the application of UAV remote …

Simple Summary To achieve precision and intelligence in farming, automatic recognition
and counting of goats are important and fundamental parts of the process of large-scale goat …

Computed tomography (CT) is an effective instrument to characterize the internal structure of
soil. However, the resolution of soil CT images is often limited by the physical properties of …

Abstract Tiny Object Detection (TOD) is a fundamental and difficult task in computer vision.
Current state-of-the-art detectors like RCNN, Fast RCNN, Faster RCNN, SSD, and YOLO …