New System for Image Object Recognition Modernizes How Computers Learn Independently and Transfer Skills
A computer vision team at the Georgia Institute of Technology has developed a new approach for computers to train themselves on image object recognition.
The work modernizes how machine learning models that are trained in one area or domain can take that knowledge and apply it to accurately recognize objects in other domains, a practice known as visual domain adaptation. An example could be a computer capturing driving scenes from a massive open-world game like Grand Theft Auto 5 and using those to understand real-world objects on the road.
“Applications for this work are limitless when talking about how a machine could take one image set from a domain and apply it anywhere,” said Viraj Prabhu, Ph.D. student in computer science and co-lead author on the work.