#computer vision

[prosthetic-placebo]

[rislas]

Termovision HUD from The Terminator (1984) A head-up display (HUD) is a transparent display that presents data over a visual screen. A Termovision refers to HUD used by Terminators to display analyses and decision options.

[tequibo]

bird?

[neuro-worm]

it works!!

[funeral]

Amanda Wasielewski, Computational Formalism: Art History and Machine Learning

[cf-12]

Flexible circuit boards manufacturing (JLCPCB, 2023)

Inkjet print head uses a fiducial camera for registering an FPC panel, and after alignment it prints graphics with UV-cureable epoxy in two passes

[nuadox]

New vision-based system helps machines develop body awareness

- By Nuadox Crew -

Researchers at MIT have developed a new vision-based system that allows machines to model their own physical structure—essentially enabling robots to “understand” their bodies without external sensors.

Published in Science Robotics, the system uses a camera mounted on a robot’s hand to watch its own movements. From this visual data, a neural network learns a self-model that can be used to simulate physical interactions, navigate space, and plan movements more effectively.

This approach bypasses the need for predefined physics models or manual calibration. The result is a more adaptive, resilient robot that can function in dynamic or unfamiliar environments—potentially accelerating development in autonomous systems and soft robotics.

The team says this method could lead to robots that are easier to train and more capable of adjusting to physical wear, damage, or manufacturing variability.

Image: Qualitative results demonstrating robustness in out-of-distribution scenarios. Credit: Nature (2025). DOI: 10.1038/s41586-025-09170-0.

Header image: A 3D-printed robotic arm grips a pencil while training through random motions and a single camera, using a system called Neural Jacobian Fields (NJF). Instead of depending on sensors or manually coded models, NJF enables robots to learn how their bodies respond to motor commands through visual observation alone—paving the way for more adaptable, cost-effective, and self-aware machines. Credit: Image courtesy of the researchers.

Scientific paper: Sizhe Lester Li et al, Controlling diverse robots by inferring Jacobian fields with deep networks, Nature (2025). DOI: 10.1038/s41586-025-09170-0

Read more at MIT News

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[historysurvivalguide]

How do you read a scroll you can’t open?

With lasers!

In 79 AD, Mount Vesuvius erupts and buries the library of the Villa of the Papyri in hot mud and ash

The scrolls are carbonized by the heat of the volcanic debris. But they are also preserved. For centuries, as virtually every ancient text exposed to the air decays and disappears, the library of the Villa of the Papyri waits underground, intact

Then, in 1750, our story continues:

While digging a well, an Italian farm worker encounters a marble pavement. Excavations unearth beautiful statues and frescoes – and hundreds of scrolls. Carbonized and ashen, they are extremely fragile. But the temptation to open them is great; if read, they would more than double the corpus of literature we have from antiquity.

Early attempts to open the scrolls unfortunately destroy many of them. A few are painstakingly unrolled by an Italian monk over several decades, and they are found to contain philosophical texts written in Greek. More than six hundred remain unopened and unreadable.

Using X-ray tomography and computer vision, a team led by Dr. Brent Seales at the University of Kentucky reads the En-Gedi scroll without opening it. Discovered in the Dead Sea region of Israel, the scroll is found to contain text from the book of Leviticus.

This achievement shows that a carbonized scroll can be digitally unrolled and read without physically opening it.

But the Herculaneum Papyri prove more challenging: unlike the denser inks used in the En-Gedi scroll, the Herculaneum ink is carbon-based, affording no X-ray contrast against the underlying carbon-based papyrus.

To get X-rays at the highest possible resolution, the team uses a particle accelerator to scan two full scrolls and several fragments. At 4-8µm resolution, with 16 bits of density data per voxel, they believe machine learning models can pick up subtle surface patterns in the papyrus that indicate the presence of carbon-based ink

In early 2023 Dr. Seales’s lab achieves a breakthrough: their machine learning model successfully recognizes ink from the X-ray scans, demonstrating that it is possible to apply virtual unwrapping to the Herculaneum scrolls using the scans obtained in 2019, and even uncovering some characters in hidden layers of papyrus

On October 12th: the first words have been officially discovered in the unopened Herculaneum scroll! The computer scientists won 40,000 dollars for their work and have given hope that the 700,000 grand prize is within reach: to read an entire unwrapped scroll!

The grand prize: first team to read a scroll by December 31, 2023

Vesuvius Challenge

A $1,000,000+ machine learning and computer vision competition