Spatial data now underpin a wide array of critical applications from environmental monitoring and urban planning to public health management and resource allocation. Advances in geospatial ...

Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

Vision-language models (VLMs) are advanced computational techniques designed to process both images and written texts, making predictions accordingly. Among other things, these models could be used to ...

Jeremy Goecks (left) is the Assistant Center Director for Research Informatics at the Moffitt Cancer Center (FL, USA), where he is also an Associate Faculty Member in the Department of Machine ...

Robbyant, an embodied AI company within Ant Group, today open-sourced LingBot-Depth, a high-precision spatial perception model designed to enhance robots’ depth sensing and 3D environmental ...

The standard facilitates the representation of geometry, topology, semantics, and appearance attributes, so that urban objects can be interpreted meaningfully by different software systems. By ...

SAN FRANCISCO, CA / ACCESS Newswire / January 22, 2026 / Nucleus4D (Nucleus), a spatial computing company operating at the intersection of real estate, immersive media, and artificial intelligence, ha ...

Over the last decade, spatial capture–recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal ...

Google DeepMind has released D4RT, a unified AI model for 4D scene reconstruction that runs 18 to 300 times faster than ...