A research team from the Gwangju Institute of Science and Technology (GIST) has unveiled an artificial intelligence (AI) technology that learns the sense of force humans feel when touching objects.

Abstract: Visual reinforcement learning (VRL) aims to learn optimal policies directly from pixel data, which holds significant potential for applications in control systems characterized by data ...

Humans don't just passively observe; we actively engage with visual information, sketching, highlighting, and manipulating it to understand. OpenThinkIMG aims to bring this interactive visual ...

This study presents experiments suggesting intriguing mesoscale reorganization of functional connectivity across distributed cortical and subcortical circuits during learning. The approach is ...

Abstract: In recent years, visual relocalization has emerged as a pivotal task in the domains of 3D computer vision and learning based methodologies, witnessing substantial advances due to the ...

Embedding models act as bridges between different data modalities by encoding diverse multimodal information into a shared dense representation space. There have been advancements in embedding models ...

ISTELive25 was another energetic and inspiring conference, held in San Antonio this year with hundreds of sessions and exhibitors enjoying the learning and networking. The exhibit hall showcased ...

Bees’ remarkable visual learning abilities make them ideal for studying active information acquisition and representation. Here, we develop a biologically inspired model to examine how flight ...