In the rapidly evolving fields of computer vision (CV) and machine learning (ML), both software frameworks and hardware ...

Image-based recognition using convolutional neural networks (CNNs), especially architectures like ResNet and YOLO, dominate ...

Studies leveraging NIR and CNNs report accuracies exceeding 95%, with some achieving perfect classification for pure fibers.

Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While leveraging multi-modal RGB and depth data is a promising solution, existing ...

A team of computer science students from Caleb University has emerged champion at the Bells University of Technology ...

WorkTango analyzed McKinsey & Company survey data to determine which five AI technologies are most commonly used in ...

Bhavyateja Potineni's research highlights the transformative potential of AI-powered computer vision in medical imaging. By ...

In the modern digital transformation era, automotive safety has undergone a paradigm shift with the rise of vision-based safety systems. Mayank Rai, an expert in automotive technology, presents a ...

GlobalSpec recently had the opportunity to ask Szymon Chawarski, product line manager at Teledyne Vision Solutions, about the growing role of AI in machine vision systems and cameras. Chawarski is the ...

GlobalSpec recently had the opportunity to ask Szymon Chawarski, product line manager at Teledyne DALSA, about the growing ...