The paper, titled "Learning from Simulated and Unsupervised Images through Adversarial Training," focused on advanced image recognition techniques and the use of both simulated and real images to train an advanced AI image program.
Apple's research paper was accepted to the 2017 Conference on Computer Vision and Pattern Recognition (CVPR) back in July, and as it turns out, Apple's work won a "CVPR 2017 Best Paper Award," coveted in the machine learning field.
MacRumors reader Tom, who holds a PhD in the field, says that CVPR is the most influential AI/machine learning conference, and that winning the award is a rare achievement "even for the top people in the field."
The paper was written by Apple researchers Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, and Russell Webb.
In addition to publishing research papers, Apple's AI and machine learning teams now maintain a Machine Learning Journal, detailing the work of Apple's engineers. The blog was just updated this week with articles that were shared at Interspeech 2017 in Stockholm, Sweden.