Standard
Rove-Tree-11 : The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research. / Hunt, Roberta Eleanor; Steenstrup Pedersen, Kim.
Computer Vision – ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I. Springer, 2023. s. 2967-2983 (Lecture Notes in Computer Science, Bind 13841).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Hunt, RE & Steenstrup Pedersen, K 2023, Rove-Tree-11: The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research. i Computer Vision – ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I. Springer, Lecture Notes in Computer Science, bind 13841, s. 2967-2983, 16th Asian Conference on Computer Vision, ACCV 2022, Macao, Kina, 04/12/2022.
APA
Hunt, R. E., & Steenstrup Pedersen, K. (2023). Rove-Tree-11: The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research. I Computer Vision – ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I (s. 2967-2983). Springer. Lecture Notes in Computer Science Bind 13841
Vancouver
Hunt RE, Steenstrup Pedersen K. Rove-Tree-11: The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research. I Computer Vision – ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I. Springer. 2023. s. 2967-2983. (Lecture Notes in Computer Science, Bind 13841).
Author
Hunt, Roberta Eleanor ; Steenstrup Pedersen, Kim. / Rove-Tree-11 : The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research. Computer Vision – ACCV 2022: 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I. Springer, 2023. s. 2967-2983 (Lecture Notes in Computer Science, Bind 13841).
Bibtex
@inproceedings{65b97da6492e4203b5b83ba4bb6ef1a4,
title = "Rove-Tree-11: The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research",
abstract = "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.",
author = "Hunt, {Roberta Eleanor} and {Steenstrup Pedersen}, Kim",
year = "2023",
language = "English",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "2967--2983",
booktitle = "Computer Vision – ACCV 2022",
address = "Switzerland",
note = "16th Asian Conference on Computer Vision, ACCV 2022 ; Conference date: 04-12-2022 Through 08-12-2022",
}
RIS
TY - GEN
T1 - Rove-Tree-11
T2 - 16th Asian Conference on Computer Vision, ACCV 2022
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.
M3 - Article in proceedings
T3 - Lecture Notes in Computer Science
SP - 2967
EP - 2983
BT - Computer Vision – ACCV 2022
PB - Springer
Y2 - 4 December 2022 through 8 December 2022
ER -
