Results 211 to 220 of about 427,529 (281)
Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Regulatory effects of winter Morchella esculenta cultivation on the summer maize phyllosphere microbiome and plant health-related traits. [PDF]
Liu G +5 more
europepmc +1 more source
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li +6 more
wiley +1 more source
Ergodicity and regime recoverability in finite Markov-modulated random walks. [PDF]
Pambukyan A, Saudagar AKJ, Kumar S.
europepmc +1 more source
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
Designing a novel radial basis neural structure for solving the dynamical hepatitis C virus model. [PDF]
Sabir Z +5 more
europepmc +1 more source
A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley +1 more source

