Abstract Nowadays, Unmanned Aerial Vehicles (UAVs) have become useful for various civil
applications, such as traffic monitoring and smart parkings, where real-time vehicle detection …

The detection of the objects in the ariel image has a significant impact on the field of parking
space management, traffic management activities and surveillance systems. Traditional …

Increased traffic density, combined with global population development, has resulted in
increasingly congested roads, increased air pollution, and increased accidents. Globally, the …

Vehicle detection and classification are the most significant and challenging activities of an
intelligent traffic monitoring system. Traditional methods are highly computationally …

Unmanned aerial vehicles (UAVs) can be used to monitor traffic in a variety of settings,
including security, traffic surveillance, and traffic control. Numerous academics have been …

Panoptic segmentation combines instance and semantic predictions, allowing the detection
of countable objects and different backgrounds simultaneously. Effectively approaching …

Vehicle classification is a hot computer vision topic, with studies ranging from ground-view to
top-view imagery. Top-view images allow understanding city patterns, traffic management …

Object detection in aerial images has been an active research area thanks to the vast
availability of unmanned aerial vehicles (UAVs). Along with the increase of computational …

There is a growing need for algorithms to automatically detect objects in satellite images.
Object detection algorithms using deep learning have demonstrated a significant …

Monitoring traffic is of vital relevance in our modern scenario. Over the years, standard ways
of capturing data, such as induction loops and camcorders, were applied for this aim …