Much of the innovation in image recognition relies on deep learning technology, an advanced type of machine learning and artificial intelligence. Typical machine learning takes in data, pushes it ...

Machine strengths. Machine learning already does much better on simple images that only have one thing in the frame. "The systems are getting to be as good as an untrained human," Platt claims.

The company has also invested in image recognition with a project that identified 10 million images pulled from YouTube videos ... The success of machine learning can be judged not in terms of ...

This essay on the lessons we learned about deep learning systems and gender recognition is one part of a three-part examination of issues relating to machine vision technology. See also: Interactive: ...

Artificial Intelligence (AI) and Machine Learning (ML) have become foundational technologies in the field of image processing. Traditionally, AI image recognition involved algorithmic techniques ...

Advanced capabilities for image retrieval and processing are relatively new and powered to a large extent by advances in machine learning technology. We present a brief history of this space, and ...

Image processing is used in a variety of use cases today, including visualisation, pattern recognition, segmentation, image information extraction, classification, and many others. Image processing ...

For over a decade, researchers have considered boson sampling—a quantum computing protocol involving light particles—as a key milestone toward demonstrating the advantages of quantum methods over ...

These machine learning systems are then fed pictures from ImageNet and its ilk, proprietary images (aka Google Photos) or other sources (like anonymized, indexed clinical records).

This year’s judges for ENR’s photo contest were shadowed by a machine-learning, artificial-intelligence system being developed to flag safety hazards in construction photos and video.