Unmanned aerial vehicles (UAVs), more commonly known as drones, are increasingly used
as a technological support tool for search-and-rescue (SAR) operations and also for post …

Convolutional neural networks (CNNs) have achieved remarkable performance in various
computer vision tasks, including object detection. However, for object detection from …

YOLOv5 is an excellent object-detection model. However, it fails to fully use multiscale
information when detecting objects with significant scale variations. It might use irrelevant …

In the context of Intelligent Transportation Systems (ITS), the role of vehicle detection and
classification is indispensable for streamlining transportation management, refining traffic …

Deploying object detectors in embedded devices such as unmanned aerial vehicles (UAVs)
comes with many challenges. This is due to both the UAV itself having low embedded …

In response to the current challenges fire detection algorithms encounter, including low
detection accuracy and limited recognition rates for small fire targets in complex …

With the continuous advancement of autonomous vehicle technology, the recognition of
buildings becomes increasingly crucial. It enables autonomous vehicles to better …

In this work, we present an uncertainty-based method for sensor fusion with camera and
radar data. The outputs of two neural networks, one processing camera and the other one …

This article presents a vision-based detection system for a micro-UAV, which has been
implemented in parallel to an autonomous GPS-based mission. The research seeks to …

The swift and accurate identification of weaponry holds paramount importance in military
operations to ensure the safety of personnel and the effectiveness of missions. In recent …