A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because ...

Stanford Medicine researchers found that a smartphone could monitor patients with two types of muscular dystrophy as well as ...

The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...

Join 10,000+ vision professionals driving innovation in automation, AI and imaging with: New 3D mapping framework combines machine vision and lidar to enhance collision detection and improve safety ...

While puzzling captchas—from dogs in hats to sliding jockstraps—still exist, most bot-deterring challenges have vanished into ...

AI transformation isn’t about tools — it’s about redesigning work, building new operating models, and helping people thrive alongside intelligent systems.

A survey of reasoning behaviour in medical large language models uncovers emerging trends, highlights open challenges, and introduces theoretical frameworks that enhance reasoning behaviour ...

Data Encoding Stage: The MNIST dataset contains grayscale handwritten digit images. Each image is scaled and normalized, then mapped to eight qubits through Angle Encoding or Amplitude Encding. This ...

Discover how AI-driven particle vision analysis is revolutionizing smart manufacturing. This review article explores cutting-edge advancements in ...

Brazilian researchers have developed a technique that estimates the force exerted on each grain of sand in a dune from images ...

Foundation models have emerged as a transformative paradigm in artificial intelligence, achieving state-of-the-art performance across natural language ...

Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...