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Researchers have developed a deep-learning algorithm that can de-noise images to reveal otherwise invisible details. To enter the world of the fantastically small, the main currency is either a ray of light or electrons. Strong beams, which yield clearer images, are damaging to specimens. On the other hand, weak beams can give noisy, low-resolution images. “Images taken with low-powered beams can be noisy, which can hide interesting and valuable visual details of biological specimens,” says Shuiwang Ji, associate professor in the department of computer science and engineering at Texas A&M...

Evolutionary Computation Poised to Provide the Next Generation of Advances in AI Written by AZoRoboticsJan 20 2021 From a pair of simple principles of evolution--chance mutation and natural selection--nature has constructed an almost unfathomable richness of life around us. Despite our scientific sophistication, human design and engineering have struggled to emulate nature's techniques and her inexhaustible inventiveness. But that may be changing. In a new perspective article, Stephanie Forrest and Risto Miikkulainen explore a domain known as evolutionary computation (EC), in which aspects of...

 E-Mail IMAGE: Optical flow field (blue arrows) when the drone flies straight forward. In the flight direction, the flow is smallest, making the tree in the drone's path the hardest one to... view more  Credit: MAVLab/ TU Delft If you ever saw a honeybee hopping elegantly from flower to flower or avoiding you as you passed by, you may have wondered how such a tiny insect has such perfect navigation skills. These flying insects' skills are partially explained by the concept of optical flow: they perceive the speed with which objects move through their field of view. Robotics research...

 E-Mail IMAGE: New research offers clues to what goes on inside the minds of machines as they learn to see. A method developed by Cynthia Rudin's lab reveals how much a neural... view more  Credit: Courtesy of Zhi Chen, Duke University DURHAM, N.C. -- The artificial intelligence behind self-driving cars, medical image analysis and other computer vision applications relies on what's called deep neural networks. Loosely modeled on the brain, these consist of layers of interconnected "neurons" -- mathematical functions that send and receive information -- that "fire" in response to fe...

Date Time Accurate Neural Network Computer Vision Without ‘Black Box’ New research offers clues to what goes on inside the minds of machines as they learn to see. A method developed by Duke’s Cynthia Rudin reveals how much a neural network calls to mind different concepts as an image travels through the network’s layers. DURHAM, N.C. — The artificial intelligence behind self-driving cars, medical image analysis and other computer vision applications relies on what’s called deep neural networks. Loosely modeled on the brain, these cons...