Image Sensor Doubles as a Neural Net

#News(IoTStack) [ via IoTGroup ]

Headings…
Image Sensor Doubles as a Neural Net
AI Researchers Propose a Machine Vision Turing Test
Bringing Eyes to the Internet of Things
Alphabet’s DeepMind Makes a Key Advance in Computer Vision

Auto extracted Text……

Image Sensor Doubles as a Neural Net
The device analyzes images thousands of times faster than conventional machine-vision strategies
A new ultra-fast machine-vision device can process images thousands of times faster than conventional techniques with an image sensor that is also an artificial neural network.
Machine vision technology often uses artificial neural networks to analyze images.
In artificial neural networks, components dubbed “neurons” are fed data and cooperate to solve a problem, such as recognizing images.
The neural net repeatedly adjusts the strength of the connections or “synapses” between its neurons and sees if the resulting patterns of behavior are better at solving the problem.
Machine vision technology often experiences delays from how cameras have to scan pixels row by row, convert video frames to digital signals and transmit such data to computers for analysis.
Lukas Mennel, an electrical engineer at TU Wien, and his colleagues sought to speed up machine vision by cutting out the middleman—they created an image sensor that itself constitutes an artificial neural network that can simultaneously acquire and analyze images.
The sensor consists of an array of pixels that each represents a neuron.
The scientists then created a neural network based on links between these photodiodes that they could train to, for instance, classify images as either the letters “n,” “v,” or “z.”
“Our image sensor does not consume any electrical power when it is operating,” Mennel says.
In experiments, the researchers used lasers to project the letters “v” and “n” onto the neural network image sensor.
Conventional machine vision technology is usually capable of processing up to 100 frames per second, with some faster systems capable of working up to 1,000 frames per second, Mennel says.
In principle, this strategy could work on the order of picoseconds, or trillionths of a second, or three to four orders of magnitude faster than currently demonstrated, he says

Read More..
AutoTextExtraction by Working BoT using SmartNews 1.02976805238 Build 26 Aug 2019