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New Technique Helps AI Extract 3D Information from 2D Images

Photos are known as two-dimensional (2D), but autonomous vehicles and other technologies have to guide the three-dimensional (3D) world. ....

Tianfu Wu , Skyla Baily , Carolina State University , Study Co , Image Credit , North Carolina State , Study Co Author , Associate Professor , Computer Engineering , Automation Industry Focus ,

From 2D to 3D through AI: Imaging technique from NCSU could boost autonomous tech

Researchers have developed a new method to help artificial intelligence (AI) extract 3D information from 2D images, making cameras more useful tools for these emerging technologies. ....

France General , Guo Jun Qi , Kelvin Cheng , Xianpeng Liu , Nan Xue , Tianfu Wu , Carolina State University , Ant Group , Seattle Research Center , National Science Foundation , International Conference On Computer Vision , Us Army Research Office , University Of Central Florida , Westlake University , North Carolina State , Object Detection , Bounding Box Denoising , International Conference , Computer Vision , Central Florida , Research Center , Research Office ,

New method helps AI navigate 3D space using 2D images

New method helps AI navigate 3D space using 2D images
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Tianfu Wu , Xianpeng Liu , Carolina State University , North Carolina State , Object Detection , Bounding Box Denoising ,

Method improves vision transformer AI system efficiency

North Carolina State researchers are working on improving vision transformers' (ViTs) efficiency so they can simplify their computing power and make their decision-making abilities more transparent. ....

North Carolina , United States , North Carolina State University , Tianfu Wu , Carolina State University , Carolina State , North Carolina State ,

New method improves efficiency of 'vision transformer' AI systems

Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images however, there are significant challenges related to both computing power requirements and decision-making transparency. Researchers have now developed a new methodology that addresses both challenges, while also improving the ViT s ability to identify, classify and segment objects in images. ....

British Columbia , Thomas Paniagua , Ryan Grainger , Naresh Cuntoor , Tianfu Wu , Us Army Research Office , National Science Foundation , Carolina State University , National Intelligence , North Carolina State , Learning Patch To Cluster Attention , Vision Transformers , Computer Vision , Pattern Recognition , Mun Wai Lee , Research Office ,