An algorithm indexed photos, ads, and other images embedded in 170 years of American newspapers. Created by researchers at the University of Washington and U.S. Library of Congress, Newspaper Navigator uses object recognition to organize visual features of newspapers dating back to 1789.

Human teachers can teach more effectively by adjusting their methods in response to student feedback. It turns out that teacher networks can do the same.

A machine learning model is scanning the oceans for the glint of garbage. Researchers from the UK’s Plymouth Marine Laboratory trained a model to identify ocean-borne refuse.

Recognizing stop signs, with their bold color scheme and distinctive shape, ought to be easy for computer vision — but it turns out to be a tricky problem. Tesla pulled back the curtain on what it takes to train its self-driving software to perform this task and others.

Deep learning promises to help emergency responders find their way through disaster zones. MIT researchers developed a tool that maps where hurricanes and other calamities have wiped out roads, helping to show aid workers the fastest ways to get to people in need.

Robot vacuum cleaners are pretty good at navigating rooms, but they still get stuck in tight spaces. New work takes a step toward giving them the smarts they’ll need to escape the bathroom.

Given real-world constraints on memory and processing time, images are often downsampled before they’re fed into a neural network. But the process removes fine details, and that degrades accuracy. A new technique squeezes images with less compromise.

It’s time to stop flushing valuable data down the toilet. The Precision Health Toilet, a suite of sensors that attach to an ordinary commode, monitors human waste for input for signs of disease. It identifies individual users by scanning where the sun doesn’t shine.

Computer vision is helping construction workers keep their social distance. Smartvid.io, a service that focuses on construction sites, offers a tool that recognizes when workers get too close to each other. The tool sends distancing warnings and reports to construction superintendents.

Faced with a classification task, an important step is to browse the catalog of machine learning architectures to find a good performer. Researchers are exploring ways to do it automatically.

Batch normalization is a technique that normalizes layer outputs to accelerate neural network training. But new research shows that it has other effects that may be more important.

Are your scientist friends intimidated by machine learning? They might be inspired by a primer from one of the world’s premier tech titans. Former Google CEO Eric Schmidt and Cornell PhD candidate Maithra Raghu school scientists in machine learning in a sprawling overview.

Unexploded munitions from past wars continue to kill and maim thousands of people every year. Computer vision is helping researchers figure out where these dormant weapons are likely to be.

Glass bottles and crystal bowls bend light in strange ways. Image processing networks often struggle to separate the boundaries of transparent objects from the background that shows through them. A new method sees such items more accurately.

Neural networks revealed both how hard Covid-19 has hit the Chinese economy, and hopeful signs that a renaissance may be underway. Researchers analyzed satellite imagery, GPS signals, and social media to get a multifaceted view of the pandemic’s impact.