A carregar...
Projeto de investigação
Sem título
Financiador
Autores
Publicações
Detecting wildlife trafficking in images from online platforms: A test case using deep learning with pangolin images
Publication . Cardoso, Ana Sofia; Bryukhova, Sofiya; Renna, Francesco; Luís, Reino; Xu, Chi; Xiao, Zixiang; Correia, Ricardo; Di Minin, Enrico; Ribeiro, Joana; Vaz, Ana Sofia
E-commerce has become a booming market for wildlife trafficking, as online platforms are increasingly more
accessible and easier to navigate by sellers, while still lacking adequate supervision. Artificial intelligence
models, and specifically deep learning, have been emerging as promising tools for the automated analysis and
monitoring of digital online content pertaining to wildlife trade. Here, we used and fine-tuned freely available
artificial intelligence models (i.e., convolutional neural networks) to understand the potential of these models to
identify instances of wildlife trade. We specifically focused on pangolin species, which are among the most
trafficked mammals globally and receiving increasing trade attention since the COVID-19 pandemic. Our convolutional
neural networks were trained using online images (available from iNaturalist, Flickr and Google)
displaying both traded and non-traded pangolin settings. The trained models showed great performances, being
able to identify over 90 % of potential instances of pangolin trade in the considered imagery dataset. These
instances included the showcasing of pangolins in popular marketplaces (e.g., wet markets and cages), and the
displaying of commonly traded pangolin parts and derivates (e.g., scales) online. Nevertheless, not all instances
of pangolin trade could be identified by our models (e.g., in images with dark colours and shaded areas), leaving
space for further research developments. The methodological developments and results from this exploratory
study represent an advancement in the monitoring of online wildlife trade. Complementing our approach with
other forms of online data, such as text, would be a way forward to deliver more robust monitoring tools for
online trafficking.
Unidades organizacionais
Descrição
Palavras-chave
Contribuidores
Financiadores
Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
POR_NORTE
Número da atribuição
2021.05426.BD