Plant biology researchers at the University of Illinois and computer scientists at the University of California Irvine have developed a new method of fossil pollen identification through the combination of super-resolution microscopy and machine learning. The team, led by Dr. Surangi Punyasena and Ms. Ingrid Romero (associate professor and graduate student in Plant Biology, respectively), developed and trained three convolutional neural network models to identify fossil pollen specimens from an unknown group of legumes.
Click here for original story, Super-resolution microscopy and machine learning shed new light on fossil pollen grains
Source: Phys.org