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Weakly supervised semantic segmentation (WSSS) methods using class labels often rely on class activation maps (CAMs) to localize objects. However, traditional CAM-based methods struggle with partial activations and imprecise object…
Different techniques of Glow Discharge AES are described in this paper. The most important parameters at such investigations are: the power of VHF-field, pressure of the inert gas and concentration of the easily ionizable additive, e.g.…
Cardiac CT is often used clinically in electrophysiology to evaluate cardiac morphology. One such case is to evaluate patients with Atrial Fibrillation (AF). AF can cause regions of slow blood flow and blood stasis through the left atrial…
Identifying low-energy adsorption geometries on catalytic surfaces is a practical bottleneck for computational heterogeneous catalysis: the difficulty lies not only in the cost of density functional theory (DFT) but in proposing initial…
Fluorescence microscopy is a powerful tool for imaging biological samples with molecular specificity. In contrast, phase microscopy provides label-free measurement of the sample's refractive index (RI), which is an intrinsic optical…
The variation of blood flow characteristics caused by the probe pressure during noninvasive studies is of particular interest within the context of fundamental and applied research. It has been shown previously that the weak local pressure…
In Nature, liquids often circulate in channels textured with leaflets, cilia or porous walls that deform with the flow. These soft structures are optimized to passively control flows and inspire the design of novel microfluidic and soft…
Infrared light scattering methods have been developed and employed to non-invasively monitor human cerebral blood flow (CBF). However, the number of reflected photons that interact with the brain is low when detecting blood flow in deep…
Immunoaffinity-based liquid biopsies of circulating tumor cells (CTCs) hold great promise for cancer management, but typically suffer from low throughput, relative complexity and post-processing limitations. Here we address these issues…
Three-dimensional (3D) biomedical image sets are often acquired with in-plane pixel spacings that are far less than the out-of-plane spacings between images. The resultant anisotropy, which can be detrimental in many applications, can be…
Visual synthesis has recently seen significant leaps in performance, largely due to breakthroughs in generative models. Diffusion models have been a key enabler, as they excel in image diversity. However, this comes at the cost of slow…
In the anomaly detection field, the scarcity of anomalous samples has directed the current research emphasis towards unsupervised anomaly detection. While these unsupervised anomaly detection methods offer convenience, they also overlook…
Flow matching has recently emerged as a principled framework for learning continuous-time transport maps, enabling efficient ODE-based sampling without relying on stochastic diffusion processes. While generative modeling has shown promise…
We report on the direct measurements of fluid flow vorticity using a spatially shaped beam with a superposition of Laguerre-Gaussian modes that reports on the rotational Doppler shift from microparticles intersecting the beam focus.…
This study extends the flow measurement method initially proposed in [22] to three-dimensional scenarios, addressing the growing need for accurate and efficient non-contact flow measurement techniques in complex hydrodynamic environments.…
We describe the apparatus of a fluorescence optical microscope with both single-photon and two-photon non-diffracting light sheets excitation for large volume imaging. With special design to accommodate two different wavelength ranges…
We use Diffusing Wave Spectroscopy (DWS) to perform the first direct space- and time-resolved measurement of the dissipation rate~$\epsilon$ at the boundary of a turbulent flow. We have shown in a previous publication that this technique…
Resonant anomaly detection is a promising framework for model-independent searches for new particles. Weakly supervised resonant anomaly detection methods compare data with a potential signal against a template of the Standard Model (SM)…
We present two novel generative geometric deep learning frameworks, termed Flow Matching PointNet and Diffusion PointNet, for predicting fluid flow variables on irregular geometries by incorporating PointNet into flow matching and diffusion…
In deep tissue photoacoustic imaging the spatial resolution is inherently limited by the acoustic wavelength. We present an approach for surpassing the acoustic diffraction limit by exploiting temporal fluctuations in the sample absorption…