Related papers: A rapid nanometre-precision autocorrelator
The ICARUS T600 LAr TPC is the far detector of the Short Baseline Program at FNAL. As it will have to work at shallow depth in the Booster Neutrino Beam, a large cosmic rays background ($\sim 11$ kHz) will be present. To reduce it, precise…
Sensing light's polarization and wavefront direction enables surface curvature assessment, material identification, shadow differentiation, and improved image quality in turbid environments. Traditional polarization cameras utilize multiple…
In this paper the efficiency of direct charged particle detection with different Silicon PhotoMultiplier (SiPM) sensors has been measured to be close to 100%. Time resolution of about 20 ps has also been confirmed for sensors with an active…
We present high-speed and wide-field EUV ptychography at 13.5 nm wavelength using a table-top high-order harmonic source. By employing a scientific complementary metal oxide semiconductor (sCMOS) detector the scan time for sub-20 nm…
The depth of a visible surface of a scene is the distance between the surface and the sensor. Recovering depth information from two-dimensional images of a scene is an important task in computer vision that can assist numerous applications…
A novel and simple approach to optical wavelength measurement is presented in this paper. The working principle is demonstrated using a tunable waveguide micro ring resonator and single photodiode. The initial calibration is done with a set…
Nanoparticles are ubiquitous, and methods that reveal insights into single-particle properties are highly desired to enable their advanced characterization. Techniques that achieve label-free single-nanoparticle detection often lack…
Some applications in scientific imaging, like space-based high-precision photometry, benefit from a detailed characterization of the sensitivity variation within a pixel. A detailed map of the intra-pixel sensitivity (IPS) allows to…
The perception of transparent objects is one of the well-known challenges in computer vision. Conventional depth sensors have difficulty in sensing the depth of transparent objects due to refraction and reflection of light. Previous…
Self-supervised monocular depth estimation has been widely investigated to estimate depth images and relative poses from RGB images. This framework is attractive for researchers because the depth and pose networks can be trained from just…
We propose a new approach for combining deep-learned non-metric monocular depth with affine correspondences (ACs) to estimate the relative pose of two calibrated cameras from a single correspondence. Considering the depth information and…
There are large individual differences in physiological processes, making designing personalized health sensing algorithms challenging. Existing machine learning systems struggle to generalize well to unseen subjects or contexts and can…
The CLARO-CMOS is an application specific integrated circuit (ASIC) designed for fast photon counting with pixellated photodetectors such as multi-anode photomultiplier tubes (Ma-PMT), micro-channel plates (MCP), and silicon…
Stereopsis has widespread appeal in robotics as it is the predominant way by which living beings perceive depth to navigate our 3D world. Event cameras are novel bio-inspired sensors that detect per-pixel brightness changes asynchronously,…
Spatial resolution of depth sensors is often significantly lower compared to that of conventional optical cameras. Recent work has explored the idea of improving the resolution of depth using higher resolution intensity as a side…
Femtosecond electron microscopy produces real-space images of matter in a series of ultrafast snapshots. Pulses of electrons self-disperse under space-charge broadening, so without compression, the ideal operation mode is a single electron…
Monolithic CMOS pixel sensors offer unprecedented opportunities for fast nano-imaging through direct electron detection in transmission electron microscopy. We present the design and a full characterisation of a CMOS pixel test structure…
Image similarity metrics play an important role in computer vision applications, as they are used in image processing, computer vision and machine learning. Furthermore, those metrics enable tasks such as image retrieval, object recognition…
Analysis of X-ray Photon Correlation Spectroscopy (XPCS) data for non-equilibrium dynamics often requires manual binning of age regions of an intensity-intensity correlation function. This leads to a loss of temporal resolution and…
We apply machine learning methods to demonstrate range superresolution in remote sensing radar detection. Specifically, we implement a denoising autoencoder to estimate the distance between two equal intensity scatterers in the…