  Particle picking is a crucial first step in the computational pipeline of
single-particle cryo-electron microscopy (cryo-EM). Selecting particles from
the micrographs is difficult especially for small particles with low contrast.
As high-resolution reconstruction typically requires hundreds of thousands of
particles, manually picking that many particles is often too time-consuming.
While semi-automated particle picking is currently a popular approach, it may
suffer from introducing manual bias into the selection process. In addition,
semi-automated particle picking is still somewhat time-consuming. This paper
presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a
simple and novel approach for fast, accurate, and fully automatic particle
picking. While our approach was inspired by template matching, it is completely
template-free. This approach is evaluated on publicly available datasets
containing micrographs of $\beta$-galactosidase and keyhole limpet hemocyanin
projections.
