  Herbarium sheets are invaluable for botanical research, and considerable time
and effort is spent by experts to label and identify specimens on them. In view
of recent advances in computer vision and deep learning, developing an
automated approach to help experts identify specimens could significantly
accelerate research in this area. Whereas most existing botanical datasets
comprise photos of specimens in the wild, herbarium sheets exhibit dried
specimens, which poses new challenges. We present a challenge dataset of
herbarium sheet images labeled by experts, with the intent of facilitating the
development of automated identification techniques for this challenging
scenario.
