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Computer Vision

case-study

MotionCam-3D by Photoneo enables 3D scanning & handling of objects that are moving on an overhead conveyor without interruption. The camera provides high-quality 3D data even while the objects are moving, swinging, or slightly rotating.

Featured

ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.

How robots learn to hike

Engineers Wiki.

Most Asked Questions.

This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!

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ORGANIZATIONS.

SHAPING THE INDUSTRY.

EPFL

University

Located in Switzerland, EPFL is one of Europe’s most vibrant and cosmopolitan science and technology institutions. EPFL is Europe...

56 Posts

Photoneo

Industrial Automation

Photoneo develops industrial 3D vision, robotic intelligence software, and ...

54 Posts

High Tech Campus Eindhoven

High Tech

High Tech Campus Eindhoven is Europe's smartest square km and has the ultim...

49 Posts

Movella

Appliances, Electrical, and Electronics Manufacturing

Movella | Xsens digitizes movement.

47 Posts

ETH Zurich

University for science and technology

Freedom and individual responsibility, entrepreneurial spirit and open-​min...

43 Posts

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TAGGED WITH machine learning

EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.

Resource-sharing boosts robotic resilience

Latest Posts

ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.

How robots learn to hike

In this article, we take a look at two tinyML projects related to healthcare. The first project helps gather Mean Radiant Temperature data outdoors to protect people from extreme heat, and the other one is a solution for affordable, accurate, & rapid detection of pneumonia.

Applications of TinyML in healthcare for a safer future

Removing litter from oceans and seas is a costly and time-consuming process. As part of a European cooperative project, a team at the Technical University of Munich (TUM) is developing a robotic system that uses machine learning methods to locate and collect waste under water.

Robots collect underwater litter

Ultra-precise lasers can be used for optical atomic clocks, quantum computers, power cable monitoring, and much more. But all lasers make noise, which researchers from DTU Fotonik want to minimize using machine learning.

Closer to the perfect laser

In this episode, we talk about how a breakthrough with compact laser nano-printers can make them more accessible for researchers and how leveraging 3D printing technology and machine learning will provide essential insight for developing next-gen cochlear implants.

Podcast: 3D Printed Cochlear Implants

In this article, we take a look at two tinyML projects that have the potential to make contributions towards sustainable development goals. While the first project is about revolutionising precision farming, the second one aims to create a network of low-cost sensors for mapping carbon emissions.

TinyML unlocks new possibilities for sustainable development technologies