Related papers: StofNet: Super-resolution Time of Flight Network
Large sky surveys are increasingly relying on image subtraction pipelines for real-time (and archival) transient detection. In this process one has to contend with varying PSF, small brightness variations in many sources, as well as…
Scene motion, multiple reflections, and sensor noise introduce artifacts in the depth reconstruction performed by time-of-flight cameras. We propose a two-stage, deep-learning approach to address all of these sources of artifacts…
The rapid expansion of the Internet of Things (IoT) has revolutionized modern industries by enabling smart automation and real time connectivity. However, this evolution has also introduced complex cybersecurity challenges due to the…
We have developed a novel detector, referred to as an "$\alpha$-ToF detector", for correlated measurements of atomic masses and decay properties of low-yield, short-lived radioactive isotopes using a multi-reflection time-of-flight mass…
Two generations of a novel detector for high-resolution transmission imaging and spectrometry of fast-neutrons are presented. These devices are based on a hydrogenous fiber scintillator screen and single- or multiple-gated intensified…
The T2K ND280 upgrade aims to reduce the systematic uncertainty of the CP-violating phase, $\delta_{CP}$, to reject non-CP violation hypothesis at $3\sigma$ confidence level. A crucial component of the ND280 upgrade, alongside the Super…
Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-energy and have been massively deployed on mobile devices for the purposes like autofocus, obstacle detection, etc. However, due to their specific measurements (depth…
Video frame interpolation (VFI) is currently a very active research topic, with applications spanning computer vision, post production and video encoding. VFI can be extremely challenging, particularly in sequences containing large motions,…
During this decade, Wireless Sensor Networks (WSNs) brought an increasing interest in the industrial and research world. One of their applications is the indoor localization. The ranging, i.e. the distance evaluation mechanism between…
Wideband spectrum sensing for low-altitude monitoring is critical yet challenging due to heterogeneous protocols,large bandwidths, and non-stationary SNR. Existing data-driven approaches treat spectrograms as natural images,suffering from…
In WSN/IoT, node localization is essential to long-running applications for accurate environment monitoring and event detection, often covering a large area in the field. Due to the lower time resolution of typical WSN/IoT platforms (e.g.,…
Currently, spatiotemporal features are embraced by most deep learning approaches for human action detection in videos, however, they neglect the important features in frequency domain. In this work, we propose an end-to-end network that…
Existing stereo matching networks typically rely on either cost-volume construction based on 3D convolutions or deformation methods based on iterative optimization. The former incurs significant computational overhead during cost…
Time-frequency images (TFIs) provide a joint time-frequency representation of a signal and have become an effective tool for analyzing, characterizing, and processing non-stationary signals. Deep learning (DL) techniques have become…
The goal of non-line-of-sight (NLOS) imaging is to image objects occluded from the camera's field of view using multiply scattered light. Recent works have demonstrated the feasibility of two-bounce (2B) NLOS imaging by scanning a laser and…
Fault diagnosis plays a crucial role in maintaining the operational integrity of mechanical systems, preventing significant losses due to unexpected failures. As intelligent manufacturing and data-driven approaches evolve, Deep Learning…
In recent years, decentralized sensor networks have garnered significant attention in the field of state estimation owing to enhanced robustness, scalability, and fault tolerance. Optimal fusion performance can be achieved under fully…
Neutron capture cross-section measurements are fundamental in the study of the slow neutron capture (s-) process of nucleosynthesis and for the development of innovative nuclear technologies. One of the best suited methods to measure…
In artificial-intelligence-aided signal processing, existing deep learning models often exhibit a black-box structure, and their validity and comprehensibility remain elusive. The integration of topological methods, despite its relatively…
Indirect Time-of-Flight cameras (iToF) are low-cost devices that provide depth images at an interactive frame rate. However, they are affected by different error sources, with the spotlight taken by Multi-Path Interference (MPI), a key…