In an advancement for robotics and artificial intelligence, researchers at Chongqing University of Technology, along with their international collaborators, have developed a cutting-edge method for enhancing interaction recognition. The study, published in Cyborg and Bionic Systems, introduces the Merge-and-Split Graph Convolutional Network (MS-GCN), a novel approach specifically designed to address the complexities of skeleton-based interaction recognition.In an advancement for robotics and artificial intelligence, researchers at Chongqing University of Technology, along with their international collaborators, have developed a cutting-edge method for enhancing interaction recognition. The study, published in Cyborg and Bionic Systems, introduces the Merge-and-Split Graph Convolutional Network (MS-GCN), a novel approach specifically designed to address the complexities of skeleton-based interaction recognition.Robotics[#item_full_content]
Deal Dive: How (Re)vive grew 10x last year by helping retailers recycle and sell returned items
The fashion industry has a huge problem: Despite many returned items being unworn or undamaged, a lot, if not the majority, end up in the trash. An estimated 9.5 billion pounds of returns ended up in landfills in 2022 alone, according to data from return logistics software company Optoro. New York-based (Re)vive wants to help […]
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The fashion industry has a huge problem: Despite many returned items being unworn or undamaged, a lot, if not the majority, end up in the trash. An estimated 9.5 billion pounds of returns ended up in landfills in 2022 alone, according to data from return logistics software company Optoro. New York-based (Re)vive wants to help
© 2024 TechCrunch. All rights reserved. For personal use only.[#item_full_content]
Teams of robots have the potential of tackling far more elaborate missions than individual robots, for instance, covering long distances faster, visiting different sites simultaneously, or monitoring larger geographical areas. Platforms that combine reliable hardware and software for multi-robot applications could help to advance research in this field, facilitating the testing of robot teams in specific real-world settings.Teams of robots have the potential of tackling far more elaborate missions than individual robots, for instance, covering long distances faster, visiting different sites simultaneously, or monitoring larger geographical areas. Platforms that combine reliable hardware and software for multi-robot applications could help to advance research in this field, facilitating the testing of robot teams in specific real-world settings.[#item_full_content]
