Results 181 to 190 of about 55,666 (218)
ABSTRACT The use of Land Use Land Cover (LULC) analysis is a fundamental requirement for urban solid waste management (SWM); however, conventional LULC analysis methods are not well suited to the spatio‐temporal variability, multi‐sensor heterogeneity, and seasonal variations of highly dynamic urban environments.
Rubeena Vohra, Ashish Kumar
wiley +1 more source
Interleaved Diffractive Networks for Information Transfer Through Random Diffusers
This work presents a cascaded diffractive optical network that enables information transfer through random, unknown diffusers using passive, interleaved structured layers that mitigate scattering without digital computation. A hybrid optical‐digital version further improves robustness and reconstruction fidelity under distortions, with both simulations
Yuhang Li +4 more
wiley +1 more source
Intrinsically Design‐Rule‐Compliant Nanophotonic Inverse Design via Learned Generative Manifolds
A generative reparameterization framework for nanophotonic inverse design is introduced, restricting optimization to a learned manifold of design‐rule‐compliant geometries. Unlike conventional penalty‐based approaches, fabrication constraints are encoded intrinsically within the design representation.
Bahrem Serhat Danis +8 more
wiley +1 more source
A monochrome multi‐task diffractive optical network architecture is designed to leverage illumination‐phase multiplexing to dynamically reconfigure its output function and accurately implement a large set of complex‐valued linear transformations between an input and an output aperture.
Xiao Wang, Aydogan Ozcan
wiley +1 more source
Why Use Immersive Virtual Reality to Assess Gait in Functional Motor Disorders?
Abstract Background Functional motor disorders (FMD) are disabling conditions modulated by attentional demands. Immersive virtual reality (iVR) engages multiple attentional and sensory networks, but its application in people with FMD (PwFMD) remains limited.
Marialuisa Gandolfi +14 more
wiley +1 more source
Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals
ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman +10 more
wiley +1 more source
Review of large YOLOv8 and RT-DETR energy efficiency on edge devices for real-time detection. [PDF]
Suchý I, Turčaník M.
europepmc +1 more source
Placental Blood‐Flow Velocity Quantification From Diffusion MRI
ABSTRACT Purpose Altered placental capillary blood flow is closely linked to obstetric complications, yet quantifying capillary‐scale blood velocity remains challenging with existing imaging methods. This is partially because capillary networks form disordered microvascular beds at the voxel scale, rather than coherent, directional vessels.
ZhuangJian Yang +14 more
wiley +1 more source
Efficient Parallelization of Message Passing Neural Network Potentials for Large-Scale Molecular Dynamics. [PDF]
Xia J, Jiang B.
europepmc +1 more source
ABSTRACT Purpose 4D cardiac cine is a powerful tool for comprehensive cardiac function assessment; however, current methods rely on regular breathing and are sensitive to bulk motion and arrhythmia. We aim to develop a 4D cardiac cine approach that requires no patient cooperation and is robust to irregular breathing, bulk motion, and cardiac arrhythmia.
Ye Tian +4 more
wiley +1 more source

