Machines are rapidly gaining the ability to perceive, interpret and interact with the visual world in ways that were once ...

These systems depend heavily on data annotation to train AI/ML models that enable real-time perception and decision-making. Raw data is collected from a suite of sensors, including LiDAR, radar, ...

Analog Devices has teamed up with Antmicro to train two of ADI's Cortex-M4 microcontollers to implement AI-at-the-edge. The ...

Traditional AI-powered waste classification systems rely on supervised learning methods. These require extensive labeled ...

AutoML for Embedded is available now on Visual Studio Code Marketplace and GitHub.

Cardiovascular diseases are a leading health concern in Hong Kong, prompting many to undergo regular heart check-ups for ...

By automating the end-to-end machine learning pipeline, it empowers less-experienced developers to build high-quality models ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Explore the evolution of image annotation—from manual labeling to AI automation—powering innovations in healthcare, retail, ...

Joshua New leads an Oak Ridge National Lab team that created a computer model of nearly every building in the United States.

Key considerations for discovery in AI-focused intellectual property (IP) litigation, including an examination of a hypothetical patent infringement and trade secret misappropriation case on highly ...

Founded by Ankush Tiwari, Abhijeet Zilpelwar, and Raghu Sesha Iyengar, Pune deeptech startup pi-labs is building defensive AI ...