Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...

Multimodal sensing in physical AI (PAI), sometimes called embodied AI, is the ability for AI to fuse diverse sensory inputs, ...

In addition to improved performance from individual sensing technologies, including radar and light detection and ranging ...

Sensor fusion—the intelligent combination of data from several sensors for the purpose of improving application or system performance—has the MEMS industry abuzz with promise. With potentially ...

Sensor fusion has been around for many years and is ubiquitous in mobile device designs. Sensor fusion “fuses” data from different types of sensors to improve measurement accuracy, such as for motion ...

MatrixSpace extends its advanced, portable drone detection portfolio with the launch of the multi-sensor MatrixSpace Fusion 360, verifying threats by fusing radar, optical, and RF/Remote ID sensor ...

In the real world, multiple types of modal information originate from the external environment and interrelate to form a whole. Multi-modal data fusion technology integrates data from diverse sources ...

A key strategy for fully autonomous vehicles is the ability to fuse together inputs from multiple sensors, which is essential for making safe and secure decisions, but it’s turning out to be much ...

What are the database management system (DBMS) requirements for complex real-time sensor data fusion? What application modifications are needed if a DBMS isn’t being used? Different definitions of ...