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Unmanned Aerial Vehicles (UAVs) are crucial in Search and Rescue (SAR) missions due to their ability to monitor vast maritime areas. However, small objects often remain difficult to detect from high altitudes due to low object-to-background…
Millimeter-wave radar systems are one of the core components of the safety-critical Advanced Driver Assistant System (ADAS) of a modern vehicle. Due to their ability to operate efficiently despite bad weather conditions and poor visibility,…
Autonomous driving holds great promise in addressing traffic safety concerns by leveraging artificial intelligence and sensor technology. Multi-Object Tracking plays a critical role in ensuring safer and more efficient navigation through…
For the safety of the traveling public, the Transportation Security Administration (TSA) operates security checkpoints at airports in the United States, seeking to keep dangerous items off airplanes. At these checkpoints, the TSA employs a…
This paper presents the first machine learning based real-world demonstration for radar-aided beam prediction in a practical vehicular communication scenario. Leveraging radar sensory data at the communication terminals provides important…
We survey the current state of millimeterwave (mmWave) radar applications in robotics with a focus on unique capabilities, and discuss future opportunities based on the state of the art. Frequency Modulated Continuous Wave (FMCW) mmWave…
(Abridged) Quantitative three-dimensional (3D) position and velocity estimates obtained by passive radar will assist the Galileo Project in the detection and classification of aerial objects by providing critical measurements of range,…
The ubiquity of unmanned aerial vehicles (UAVs) or drones is posing both security and safety risks to the public as UAVs are now used for cybercrimes. To mitigate these risks, it is important to have a system that can detect or identify the…
Machine learning is increasingly critical for analysis of the ever-growing corpora of overhead imagery. Advanced computer vision object detection techniques have demonstrated great success in identifying objects of interest such as ships,…
Positional estimation is of great importance in the public safety sector. Emergency responders such as fire fighters, medical rescue teams, and the police will all benefit from a resilient positioning system to deliver safe and effective…
mmWave radar enables human sensing in non-visual scenarios-e.g., through clothing or certain types of walls-where traditional cameras fail due to occlusion or privacy limitations. However, robust anomaly detection with mmWave remains…
As litter pollution continues to rise globally, developing automated tools capable of detecting litter effectively remains a significant challenge. This study presents a novel approach that combines, for the first time, privileged…
This paper deals with the multi-object detection and tracking problem, within the scope of open Radio Access Network (RAN), for collision avoidance in vehicular scenarios. To this end, a set of distributed intelligent agents collocated with…
Comparing the observed brightness of various buried objects is a straightforward way to characterize the performance of a ground penetrating radar (GPR) system. However, a limitation arises. A simple comparison of buried object brightness…
Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to $6$-$8$ m) and are…
Detecting dangerous driving has been of critical interest for the past few years. However, a practical yet minimally intrusive solution remains challenging as existing technologies heavily rely on visual features or physical proximity. With…
Unmanned Aerial Vehicles (drones) are emerging as a promising technology for both environmental and infrastructure monitoring, with broad use in a plethora of applications. Many such applications require the use of computer vision…
For autonomous vehicles to be able to operate successfully they need to be aware of other vehicles with sufficient time to make safe, stable plans. Given the possible closing speeds between two vehicles, this necessitates the ability to…
Confidence-aware learning is proven as an effective solution to prevent networks becoming overconfident. We present a confidence-aware camouflaged object detection framework using dynamic supervision to produce both accurate camouflage map…
Aerial imaging plays a crucial role in navigation and data acquisition for unmanned aerial vehicles and satellite imaging systems. In recent days, the employment of drones has been escalated in several applications that are not limited to…