Results 121 to 130 of about 557,874 (331)
On an Ergodic Property of a Certain Class of Markov Processes [PDF]
Gopinath Kallianpur
openalex +1 more source
This study proposes RefineCatDiff, a refinement framework for high‐quality medical image segmentation. By developing a categorical distribution‐based discrete diffusion process for refinement, the framework aligns well with the characteristics of image segmentation tasks. Experimental results on multiple datasets across different modalities demonstrate
Feng Liu +8 more
wiley +1 more source
Mainstream Artificial Intelligence Technologies in Contemporary Ophthalmology
This review explores the latest artificial intelligence (AI) technologies in ophthalmology, focusing on four key data types: medical imaging, electronic health records, robotic‐assisted surgery, and genomics. It examines the structural features, use cases, clinical goals, and evaluation metrics of various AI algorithms, while also introducing emerging ...
Shiqi Yin +9 more
wiley +1 more source
Optical microscopy is commonly used to observe simple turn‐on/off phenomena in chemical reactions. A method is presented for the real‐time monitoring of diverse reaction pathways at the single‐molecule level using optical microscopy. This technique enables detailed kinetic and dynamic studies to be performed, providing new insights into catalyst design
Minsoo Park +7 more
wiley +2 more sources
Stochastic models of population growth
We considered three types of stochastic models of a single population growth: with diffusion-type noise; with parameters replaced by stochastic processes; and with random jumps describing a sudden decrease in population size.
Katarzyna Pichór, Ryszard Rudnicki
doaj +1 more source
Variability and singularity arising from a Piecewise-Deterministic Markov Process applied to model poor patient compliance in the multi-IV case. [PDF]
Fermín LJ, Lévy-Véhel J.
europepmc +1 more source
Markov processes with creation of particles [PDF]
Martin L. Silverstein
openalex +1 more source
This review outlines how recurrent neural networks model multisensory integration by capturing temporal and probabilistic features of sensory input. Key developments, challenges, and future directions are summarized, providing insights into biologically inspired AI. Multisensory integration (MSI) is a core brain function underlying perception, learning,
Ehsan Bolhasani +2 more
wiley +1 more source

