"Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2 digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decision-making scenarios."
Saturday, September 09, 2017
Can Machine Learning Overcome Absence of Lens?
Researches from University of Utah at Salt Lake City proved that AI can be somewhat successful in distinguishing between the digits as seen by image sensor with no lens. "Lensless-camera based machine learning for image classification" paper by Ganghun Kim, Stefan Kapetanovic, Rachael Palmer, and Rajesh Menon is published by arxiv.org. From the abstract:
"Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2 digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decision-making scenarios."
"Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2 digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decision-making scenarios."
No comments:
Post a Comment
All comments are moderated to avoid spam and personal attacks.