A better model would take these factors into account to offer a more realistic recommendation, perhaps by providing an option ...

Federal systems integrators face a familiar mandate in 2026 — deliver faster mission outcomes with tighter constraints — plus a new reality: agencies are moving from artificial intelligence ...

Research has focused on Multi-Modal Semantic Segmentation (MMSS), where pixel-wise predictions are derived from multiple visual modalities captured by diverse sensors. Recently, the large vision model ...

S2DM is an approach for modeling data across multiple domains. It is designed to be simple and accessible for Subject Matter Experts (SMEs) while incorporating semantic principles to define meaningful ...

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 ...

Yokogawa Electric Corporation announced that it has increased its strategic investment in Semantum Oy, a Finnish company that ...

Introduction: Picking Up the Quantum Thread In Part 1 of this two-part series, I confessed that this whole journey was ...

Abstract: Semantic 3D reconstruction from monocular imagery serves as a cost-effective tool for many urban applications, such as energy system modeling, resilience analysis, and urban planning.

Abstract: In artificial intelligence, the significance of thorough documentation of models and datasets for publication is underestimated. However, due to the rising trend in the explainability and ...

For the first time, scientists have resolved extremely intense tropical cyclones and their effect on the ocean carbon cycle in a global Earth system model. Using two category-4 hurricanes in the North ...

We introduce a geometric semantic model designed to capture fine-grained semantic representations in a multidimensional space. Building on this model, we develop a novel annotation framework that ...