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."
Can Machine Learning Overcome Absence of Lens?
Reviewed by MCH
on
September 09, 2017
Rating:
Reviewed by MCH
on
September 09, 2017
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