A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what's inside. Researchers from MIT, Amazon Robotics, ...

Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While leveraging multi-modal RGB and depth data is a promising solution, existing ...

Use precise geolocation data and actively scan device characteristics for identification. This is done to store and access information on a device and to provide personalised ads and content, ad and ...

The team has developed an animal model of relapse over the past seven ... detect an astrocyte within an image, similar to how ...

The team has developed an animal model of relapse over the past seven ... detect an astrocyte within an image, similar to how object recognition software works. "Machine learning techniques have been ...

The team has developed an animal model of relapse over the past seven ... detect an astrocyte within an image, similar to how object recognition software works. "Machine learning techniques have been ...

LOP associations are modeled by explicitly encoding object and layout information, while a Large Foundation Model (LFM) technique allows for efficient training without extensive annotations. The ...

Semantic communication is emerging as a vital technique for ensuring efficient and reliable transmission ... In this paper, we introduce the use of object-attribute-relation (OAR) as a semantic ...

The new technique relies on removing a small portion of the data used to train the AI model. "There can be significant variation in the data samples included in training datasets," Kim says. "Some of ...

This page refers to version 3.5 of the Object Model. All Duet software projects share the same object model to store configuration and sensor data. This page provides documentation about the different ...