Related papers: SiWa: See into Walls via Deep UWB Radar
We address the detection of material defects, which are inside a layered material structure using compressive sensing based multiple-input and multiple-output (MIMO) wireless radar. Here, the strong clutter due to the reflection of the…
Frequency-modulated continuous-wave (FMCW) radar is a promising sensor technology for indoor drones as it provides range, angular as well as Doppler-velocity information about obstacles in the environment. Recently, deep learning approaches…
Understanding surface material properties is crucial for enhancing indoor robot perception and indoor digital twinning. However, not all sensor modalities typically employed for this task are capable of reliably capturing detailed surface…
Simultaneous Localization and Mapping (SLAM) allows mobile robots to navigate without external positioning systems or pre-existing maps. Radar is emerging as a valuable sensing tool, especially in vision-obstructed environments, as it is…
This paper presents our approach of the radio interface problematic for Wireless Sensor Network. We introduce the WSN context and constraints associated. We propose an IR-UWB solution and illustrate why it could be a viable solution for…
Regular and uninterrupted operation of critical infrastructures such as power, transport, communication etc. are essential for proper functioning of a country. Cyber-attacks causing disruption in critical infrastructure service in the past,…
This paper details a number of indoor localization techniques developed for real-time monitoring of older adults. These were developed within the framework of the i-Light research project that was funded by the European Union. The project…
Satellite imagery is important for many applications including disaster response, law enforcement, and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the…
BACKGROUND AND PURPOSE: Deep learning has been demonstrated effective in many neuroimaging applications. However, in many scenarios, the number of imaging sequences capturing information related to small vessel disease lesions is…
Precise indoor positioning systems (IPSs) are key to perform a set of tasks more efficiently during aircraft production, operation and maintenance. For instance, IPSs can overcome the tedious task of configuring (wireless) sensor nodes in…
Smart Micro Aerial Vehicles (MAVs) have transformed infrastructure inspection by enabling efficient, high-resolution monitoring at various stages of construction, including hard-to-reach areas. Traditional manual operation of drones in…
Simultaneous Localization and Mapping (SLAM) is a key tool for monitoring construction sites, where aligning the evolving as-built state with the as-planned design enables early error detection and reduces costly rework. LiDAR-based SLAM…
Inverse Synthetic Aperture Radar (ISAR) imaging presents a formidable challenge when it comes to small everyday objects due to their limited Radar Cross-Section (RCS) and the inherent resolution constraints of radar systems. Existing ISAR…
Indoor positioning systems (IPS) are emerging technologies due to an increasing popularity and demand in location based service (LBS). Because traditional positioning systems such as GPS are limited to outdoor applications, many IPS have…
3D anomaly detection has recently become a significant focus in computer vision. Several advanced methods have achieved satisfying anomaly detection performance. However, they typically concentrate on the external structure of 3D samples…
Waveguide-integrated plasmonics is a growing field with many innovative concepts and demonstrated devices in the visible and near-infrared. Here, we extend this body of work to the mid-infrared for the application of surface-enhanced…
Wireless sensing technology has become prevalent in healthcare, smart homes, and autonomous driving due to its non-contact operation, penetration capabilities, and cost-effectiveness. As its applications expand, the technology faces…
In this work, we present a comparison of a shallow and a deep learning architecture for the automated segmentation of white matter lesions in MR images of multiple sclerosis patients. In particular, we train and test both methods on early…
Recent years have witnessed the great success of deep learning algorithms in the geoscience and remote sensing realm. Nevertheless, the security and robustness of deep learning models deserve special attention when addressing…
Advances in machine learning and deep neural networks for object detection, coupled with lower cost and power requirements of cameras, led to promising vision-based solutions for sUAS detection. However, solely relying on the visible…