To address the trade-off between accuracy and cross-city generalization in traffic flow estimation, a research team from The ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

IIT-Bombay's SpADANet uses AI for improved, spatially aware cyclone damage assessment, enhancing accuracy even with limited ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Spatial transcriptomics (ST) technologies reveal the spatial organization of gene expression in tissues, providing critical insights into ...

A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...

Molmo 2 is an 8B-parameter model that surpasses the 72B-parameter Molmo in accuracy, temporal understanding, and pixel-level ...

Physical AI converts terrain, drainage, soil variability and sunlight into structured inputs that can be simulated, ...

The partnership addresses a critical vulnerability in modern operations: GPS unavailability, spoofing, interference, and jamming. When satellite signals are compromised, autonomous systems and field ...

Network-wide traffic flow, which represents the dynamic traffic volumes on each link of a road network, is fundamental to smart cities. However, the ...

Debuting Next-Gen Robotics Powering Precise Indoor-Outdoor Navigation, Geomagnetic Mapping, and Real-Time Tracking ...