TY - GEN

T1 - Rove-Tree-11

T2 - The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research

AU - Hunt, Roberta Eleanor

AU - Steenstrup Pedersen, Kim

PY - 2023

Y1 - 2023

N2 - We present a new dataset of images of pinned insects from museum collections along with a ground truth phylogeny (a graph representing the relative evolutionary distance between species). The images include segmentations, and can be used for clustering and deep hierarchical metric learning. As far as we know, this is the first dataset released specifically for generating phylogenetic trees. We provide several benchmarks for deep metric learning using a selection of state-of-the-art methods.

AB - We present a new dataset of images of pinned insects from museum collections along with a ground truth phylogeny (a graph representing the relative evolutionary distance between species). The images include segmentations, and can be used for clustering and deep hierarchical metric learning. As far as we know, this is the first dataset released specifically for generating phylogenetic trees. We provide several benchmarks for deep metric learning using a selection of state-of-the-art methods.

UR - http://doi.org/10.17894/ucph.39619bba-4569-4415-9f25-d6a0ff64f0e3

UR - https://github.com/robertahunt/Rove-Tree-11

M3 - Article in proceedings

SP - 2967

EP - 2983

BT - Proceedings of the Asian Conference on Computer Vision (ACCV

PB - Springer

ER -