Blount, D.,Minton, G.,Khan, Christin B.,Levenson, Jacob,Dulau, Violaine,Gero, S.,Parham, J.,Holmberg, Jason
Document presented to the Scientific Committee of the International Whaling Commission no. 330, 2020.
Abstract | Links | BibTeX | Tags: Arabian Sea, Artificial intelligence, Flukebook, humpback dolphin, Humpback Whale, Indian Ocean, matching, megaptera novaeangliae, methodology, Oman, photo identification, Sousa chinensis
@techreport{,
title = {Flukebook – Continuing growth and technical advancement for cetacean photo identification and data archiving, including automated fin, fluke, and body matching},
author = {Blount, D.,Minton, G.,Khan, Christin B.,Levenson, Jacob,Dulau, Violaine,Gero, S.,Parham, J.,Holmberg, Jason},
url = {https://arabianseawhalenetwork.org/wp-content/uploads/2020/06/sc_68b_ph_06_flukebook-developments-incl-aswn-and-indocet-1.pdf},
year = {2020},
date = {2020-01-01},
journal = {Paper presented to the meeting of the Scientific Committee of the International Whaling Commission},
number = {330},
pages = {13},
publisher = {IWC},
institution = {Document presented to the Scientific Committee of the International Whaling Commission},
abstract = {Flukebook (flukebook.org) is a non-profit, open source cetacean data archiving and
photo-identification tool developed under the larger Wildbook platform (wildbook.org) that uses
computer vision and machine learning to facilitate automated identification of individual animals
in the wild. In 2016, the IWC approved funding for the development of a regional data platform
for the Arabian Sea Whale Network (ASWN) to be implemented in collaboration with Wild Me
(wildme.org), the software and machine learning developers of Flukebook. This foundational
collaboration expanded the capabilities of Flukebook and served as the springboard for
subsequent years of growth in data and usage (e.g., by regional consortiums), as well as
significant technical improvements in 2019-2020 in the application of computer vision and
machine learning, specifically for North Atlantic and Southern right whales, humpback whales,
sperm whales, and multiple species of dolphins. Ongoing improvements in our community
support model and technical advances are bringing together industry, governmental, and NGO
collaborators in a global-scale platform for cetacean research.},
keywords = {Arabian Sea, Artificial intelligence, Flukebook, humpback dolphin, Humpback Whale, Indian Ocean, matching, megaptera novaeangliae, methodology, Oman, photo identification, Sousa chinensis},
pubstate = {published},
tppubtype = {techreport}
}
Flukebook (flukebook.org) is a non-profit, open source cetacean data archiving and
photo-identification tool developed under the larger Wildbook platform (wildbook.org) that uses
computer vision and machine learning to facilitate automated identification of individual animals
in the wild. In 2016, the IWC approved funding for the development of a regional data platform
for the Arabian Sea Whale Network (ASWN) to be implemented in collaboration with Wild Me
(wildme.org), the software and machine learning developers of Flukebook. This foundational
collaboration expanded the capabilities of Flukebook and served as the springboard for
subsequent years of growth in data and usage (e.g., by regional consortiums), as well as
significant technical improvements in 2019-2020 in the application of computer vision and
machine learning, specifically for North Atlantic and Southern right whales, humpback whales,
sperm whales, and multiple species of dolphins. Ongoing improvements in our community
support model and technical advances are bringing together industry, governmental, and NGO
collaborators in a global-scale platform for cetacean research.
photo-identification tool developed under the larger Wildbook platform (wildbook.org) that uses
computer vision and machine learning to facilitate automated identification of individual animals
in the wild. In 2016, the IWC approved funding for the development of a regional data platform
for the Arabian Sea Whale Network (ASWN) to be implemented in collaboration with Wild Me
(wildme.org), the software and machine learning developers of Flukebook. This foundational
collaboration expanded the capabilities of Flukebook and served as the springboard for
subsequent years of growth in data and usage (e.g., by regional consortiums), as well as
significant technical improvements in 2019-2020 in the application of computer vision and
machine learning, specifically for North Atlantic and Southern right whales, humpback whales,
sperm whales, and multiple species of dolphins. Ongoing improvements in our community
support model and technical advances are bringing together industry, governmental, and NGO
collaborators in a global-scale platform for cetacean research.