相关论文: A novel RF-enabled Non-Destructive Inspection Meth…

Lately a new approach to Extended Reality (XR), denoted as XR-RF, has been proposed which is realized by combining Radio Frequency (RF) Imaging and programmable wireless environments (PWEs). RF Imaging is a technique that aims to detect…

Nondestructive evaluation (NDE) techniques are widely used to detect flaws in critical components of systems like aircraft engines, nuclear power plants and oil pipelines in order to prevent catastrophic events. Many modern NDE systems…

The pursuit of immersive and structurally aware multimedia experiences has intensified interest in sensing modalities that reconstruct objects beyond the limits of visible light. Conventional optical pipelines degrade under occlusion or low…

Accurate, real-time wireless signal prediction is essential for next-generation networks. However, existing vision-based frameworks often rely on computationally intensive models and are also sensitive to environmental interference. To…

Non-destructive evaluation (NDE) of rail tracks is crucial to ensure the safety and reliability of rail transportation systems. In this work, we present a quantitative study using various signal processing methods to identify defects in…

In this paper, a novel optical inspection system is presented that is directly suitable for Industry 4.0 and the implementation on IoT-devices controlling the manufacturing process. The proposed system is capable of distinguishing between…

Wind turbine blades operate in harsh environments, making timely damage detection essential for preventing failures and optimizing maintenance. Drone-based inspection and deep learning are promising, but typically depend on large, labeled…

A physics assisted deep learning framework to perform accurate indoor imaging using phaseless Wi-Fi measurements is proposed. It is able to image objects that are large (compared to wavelength) and have high permittivity values, that…

Full-waveform inversion (FWI) is an accurate imaging approach for modeling velocity structure by minimizing the misfit between recorded and predicted seismic waveforms. However, the strong non-linearity of FWI resulting from fitting…

This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technology based on wireless communication. We proposed a system based on NRF transceivers to establish a…

A current trend in industries such as semiconductors and foundry is to shift their visual inspection processes to Automatic Visual Inspection (AVI) systems, to reduce their costs, mistakes, and dependency on human experts. This paper…

As the complexity and connectivity of networks increase, the need for novel malware detection approaches becomes imperative. Traditional security defenses are becoming less effective against the advanced tactics of today's cyberattacks.…

Early-stage visual quality inspection is vital for achieving Zero-Defect Manufacturing and minimizing production waste in modern industrial environments. However, the complexity of robust visual inspection systems and their extensive data…

Full-waveform inversion (FWI) is a powerful geophysical imaging technique that infers high-resolution subsurface physical parameters by solving a non-convex optimization problem. However, due to limitations in observation, e.g., limited…

The rapid evolution of wearable technologies, such as AR glasses, demands compact, energy-efficient sensors capable of high-precision measurements in dynamic environments. Traditional Frequency-Modulated Continuous Wave (FMCW) Laser…

Full-waveform inversion (FWI) is a widely used technique in seismic processing to produce high resolution Earth models that fully explain the recorded seismic data. FWI is a local optimisation problem which aims to minimise in a…

Physics-informed neural networks (PINNs) provide a promising framework for solving inverse problems governed by partial differential equations (PDEs) by integrating observational data and physical constraints in a unified optimization…

In-region location verification (IRLV) aims at verifying whether a user is inside a region of interest (ROI). In wireless networks, IRLV can exploit the features of the channel between the user and a set of trusted access points. In…

We present NeWRF, a deep learning framework for predicting wireless channels. Wireless channel prediction is a long-standing problem in the wireless community and is a key technology for improving the coverage of wireless network…

Accurately mapping the radio environment (e.g., identifying wireless signal strength at specific frequency bands and geographic locations) is crucial for efficient spectrum sharing, enabling secondary users (SUs) to access underutilized…