New Zealand pollen

Dataset first used in the paper Precise automatic classification of 46 different pollen types with convolutional neural networks [0].

The images are dark field microscope images captured on the Classifynder system. The Classifynder (formerly knownas AutoStage) is documented in [1]. It was designed as a complete ’standalone’ system for automated pollen analysis. The system uses basic shape features to identify the locations of objects of interest (i.e. pollen grains) in conventional microscope slides under a low-power objective. It then switches to a higher power objective and visits the location of each pollen object to capture an image of it to be used for classification.
Objects are imaged at different focus levels, producing a ’Z-stack’. The system subsets the best-focused portions of each object Z-stack images, and then combines them to
produce a single composite image, followed by segmentation from the background. This image is then falsely colored to show depth.
[0] http://doi.org/10.1371/journal.pone.0229751[1] http://www.sciencedirect.com/science/article/pii/S0034666711001205