Author: AI Generated Robotic Content

Many computer systems people interact with on a daily basis require knowledge about certain aspects of the world, or models, to work. These systems have to be trained, often needing to learn to recognize objects from video or image data. This data often contains superfluous content that reduces the accuracy of models. So researchers found …

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Using functional near-infrared spectroscopy, a lab has captured functional brain activity as humans collaborated with robots on a manufacturing task.

Given a 3D piece of origami, can you flatten it without damaging it? Just by looking at the design, the answer is hard to predict, because each and every fold in the design has to be compatible with flattening.

With mathematical modeling, a research team has now succeeded in better understanding how the optimal working state of the human brain, called criticality, is achieved. Their results mean an important step toward biologically-inspired information processing and new, highly efficient computer technologies and have been published in Scientific Reports.

Argonne researchers have created an automatic technique that can fill in gaps in X-ray data.

By combining machine learning with the laws of physics, researchers in the lab of Matthew Lew, associate professor of electrical and systems engineering at Washington University in St. Louis, have been able to sort out the orientation and position of overlapping single molecules in 5D from a single image.

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures.