The views, information, or opinions expressed in the Industry News RSS feed belong solely to the author and do not necessarily represent those of IDEX Health & Science and its employees.
Article obtained from Photonics RSS Feed.
A single-pixel machine vision framework leverages deep-learning designed optical networks to bypass the need for an image sensor-array or digital processor. The system, developed in the lab of UCLA Chancellor’s Professor Aydogan Ozcan, paves the way for tackling certain challenges that are beyond the capabilities of current imaging and machine learning technologies.
Most machine vision systems used today use a lens-based camera that sends information to a digital processor that performs machine learning tasks. Even with modern, state-of-the-art technology, these systems suffer certain drawbacks; the video feed, by nature of the camera’s high-pixel count, contains a large volume of data, usually with redundant information….READ MORE