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 ...

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

In 2008, Pietro Perona , Caltech's Allen E. Puckett Professor of Electrical Engineering, was on sabbatical in Italy, enjoying a cappuccino in a ...

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 ...

Abstract: Road obstacles are a major contributor to traffic accidents, making their accurate detection and classification vital for road safety and infrastructure maintenance. This paper presents a ...

Abstract: Most hyperspectral image (HSI) classification methods assume that all classes in the test set are present during training. However, in real-world applications, acquiring labeled training ...