Abstract “Unmanned aerial vehicles”(UAVs) are now being used for a wide range of
surveillance applications. Specifically, the detection of on-ground vehicles from UAV images …

With increasing the market share of electric vehicles (EVs), the rechargeable lithium-ion
batteries (LIBs) as the critical energy power sources have experienced rapid growth in the …

Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

Deep neural network based techniques are state-of-the-art for object detection and
classification with the help of the development in computational power and memory …

Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing
technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their …

Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an
emerging application attracting significant attention from researchers in various areas of …

In the Machine Learning era, Deep Neural Networks (DNNs) have taken the spotlight, due to
their unmatchable performance in several applications, such as image processing, computer …

The accurate trajectory prediction is a crucial task for the autonomous vehicles that help to
plan and fast decision making capability of the system to reach their destination in the …

The Hogweed of Sosnowskyi (lat. Heracleum sosnówskyi) is poisonous for humans,
dangerous for farming crops, and local ecosystems. This plant is fast-growing and has …

Combining multiple models is a well-known technique to improve predictive performance in
challenging tasks such as object detection in UAV imagery. In this paper, we propose fusion …