Results 151 to 160 of about 497,808 (317)
GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models through Statistically-Guided Geo-Prototyping [PDF]
The problem of forecasting spatiotemporal events such as crimes and accidents is crucial to public safety and city management. Besides accuracy, interpretability is also a key requirement for spatiotemporal forecasting models to justify the decisions.
arxiv
This review explores the principles and recent advances in dynamic structural colors, including SPR, LSPR, FP, and Mie resonances. It highlights key tuning strategies involving functional materials and external stimuli, evaluating their performance and limitations.
Xinting Li+4 more
wiley +1 more source
Inspired by neuronal oscillatory activity, a neural device with intrinsic perception and decision‐making (NDIPD) is proposed. By mimicking neuronal oscillations, it enables perception and decision‐making at five mechanical stimulation points using a single interface.
Congtian Gu+11 more
wiley +1 more source
Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation [PDF]
To have a superior generalization, a deep learning neural network often involves a large size of training sample. With increase of hidden layers in order to increase learning ability, neural network has potential degradation in accuracy. Both could seriously limit applicability of deep learning in some domains particularly involving predictions of ...
arxiv
Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning. [PDF]
Zhang W+10 more
europepmc +1 more source
Label‐Free Dual‐Modal Photoacoustic/Ultrasound Localization Imaging for Studying Acute Kidney Injury
This work develops a 3D label‐free photoacoustic/super‐resolution ultrasound imaging system as a comprehensive non‐invasive tool for acute kidney injury (AKI) study. This technique visualizes the intricate structure of renal microvessels and provides critical physiological insights, including renal hemodynamics and oxygenation.
Shensheng Zhao+5 more
wiley +1 more source
Hybrid Ensemble Deep Graph Temporal Clustering for Spatiotemporal Data [PDF]
Classifying subsets based on spatial and temporal features is crucial to the analysis of spatiotemporal data given the inherent spatial and temporal variability. Since no single clustering algorithm ensures optimal results, researchers have increasingly explored the effectiveness of ensemble approaches.
arxiv
Deep learning with spatiotemporal consistency for nerve segmentation in ultrasound images
Ultrasound-Guided Regional Anesthesia (UGRA) has been gaining importance in the last few years, offering numerous advantages over alternative methods of nerve localization (neurostimulation or paraesthesia). However, nerve detection is one of the most tasks that anaesthetists can encounter in the UGRA procedure.
Hafiane, Adel+2 more
openaire +2 more sources