Skip to main content
  1. Home
  2. Emerging Tech
  3. Computing
  4. News

1990s blockbusters taught an artificial intelligence how to spot handguns

Add as a preferred source on Google

Humans are hardwired to quickly spot objects in the corner of our eyes: Kids getting into trouble, snakes slithering into the room, and the like. That task isn’t as easy for algorithms, but they’re getting better. Someday soon they may even help humans spot dangerous objects we might have missed. Researchers at the University of Granada, for example, have used deep learning to train an algorithm to identify handguns from video in real time.

The system may be used in home security systems, police body cameras, and video surveillance at places like schools, airports, and malls. It could also be applied to videos online as a way to monitor and map violent content.

Recommended Videos

Although around 30 percent of American adults say they own guns; the weapons have a steady presence in our lives. They seem to be everywhere you look — carried by cops on TV or as a key component in many of today’s most popular video games. So it’s appropriate that the University of Granada researchers trained their system on movies like Pulp Fiction, and the Mission Impossible and James Bond franchises, through which many of us also had our first introduction to firearms.

After training the algorithm on low-quality video of these classic films, it was able to effectively identify drawn handguns more than 96.5 percent, while analyzing in real time at 5 frames per second. When the algorithm spots a handgun, it borders it with a red box. The researchers think that the model can be combined with an alarm system in order to quickly and inexpensively identify firearms in places where they’re forbidden or may pose a threat.

Although the scientists don’t expect their model to completely replace current weapon-detection systems like metal detectors, they see it as a complementary system to help address some of the drawbacks of conventional methods. For example, metal detectors require guns to pass through a certain point, which — as anyone whose passed a security checkpoint knows — can create a bottleneck of people in crowded areas. The model is also able to discriminate between guns and other metal objects, which the metal detector cannot.

Dyllan Furness
Former Contributor
Dyllan Furness is a freelance writer from Florida. He covers strange science and emerging tech for Digital Trends, focusing…
Anti-surveillance clothing is getting cheaper, but don’t expect an invisibility cloak
Affordable shirts now claim to confuse facial recognition, although their protection depends heavily on the camera and software watching you
Chart, Plot, Adult

Anti-surveillance clothing is starting to look less like an art-school experiment and more like something you could actually wear outside. Shirts designed to confuse facial recognition systems now cost about as much as ordinary streetwear, although buying one won’t make you disappear.

The Guardian reports that designers are using face-like prints, unusual cuts and infrared lights to interfere with computer vision. These techniques target specific weaknesses, so their success depends on what happens to be watching you.

Read more
This spinning drone hides in plain sight using a visual illusion
This drone doesn't turn invisible. It tricks your brain into thinking it has.
Phantom Twist

For decades, engineers have chased the dream of an invisible drone. The usual approaches have involved transparent materials, camouflage coatings, or complex optical systems that bend light around an object. Researchers at Northwestern University decided to take a completely different route. Instead of hiding the drone itself, they chose to fool the human eye.

The result is Phantom Twist, an experimental drone that spins so rapidly it almost disappears into the background. It's not technically invisible, but to anyone watching, it looks more like a faint blur than a flying machine.

Read more
This smart knitted fabric can flip switches, count your steps, and even change shape
Grandma's knitting just entered its Iron Man era
Representative Image

For most of us, knitting brings to mind sweaters, scarves, and perhaps an ambitious grandmother determined to make winter more fashionable. Researchers at Harvard University, however, have a far more futuristic vision. They've transformed ordinary knitted fabric into a programmable material capable of changing shape, acting as an electrical switch, sensing movement, and potentially forming the foundation of tomorrow's wearable technology.

The research, published in Advanced Functional Materials by scientists at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), demonstrates how machine-knitted textiles can "snap" between multiple stable shapes without relying on motors or rigid mechanical parts.

Read more