  The BIOSCAN project, led by the International Barcode of Life Consortium,
seeks to study changes in biodiversity on a global scale. One component of the
project is focused on studying the species interaction and dynamics of all
insects. In addition to genetically barcoding insects, over 1.5 million images
per year will be collected, each needing taxonomic classification. With the
immense volume of incoming images, relying solely on expert taxonomists to
label the images would be impossible; however, artificial intelligence and
computer vision technology may offer a viable high-throughput solution.
Additional tasks including manually weighing individual insects to determine
biomass, remain tedious and costly. Here again, computer vision may offer an
efficient and compelling alternative. While the use of computer vision methods
is appealing for addressing these problems, significant challenges resulting
from biological factors present themselves. These challenges are formulated in
the context of machine learning in this paper.
