We are losing biodiversity at an unprecedented scale and in many cases, we do not even know the basic data for the species. Traditional methods for wildlife monitoring are inadequate. Development of new computer vision tools enables the use of images as the source of information about wildlife. Social media is the rich source of wildlife images, which come with a huge bias, thus thwarting traditional population size estimate approaches. Here, we present a new framework to take into account the social media bias when using this data source to provide wildlife population size estimates. We show that, surprisingly, this is a learnable and potentially solvable problem.
@article{arxiv.1908.01875,
title = {Animal Wildlife Population Estimation Using Social Media Images Collections},
author = {Matteo Foglio and Lorenzo Semeria and Guido Muscioni and Riccardo Pressiani and Tanya Berger-Wolf},
journal= {arXiv preprint arXiv:1908.01875},
year = {2019}
}
Comments
KDD19 Workshop on Data Mining and AI for Conservation, Earth Day (5 August 2019), Anchorage, AL