Deep Visual-Genetic Biometrics for Taxonomic Classification of Rare Species. (arXiv:2305.06695v1 [cs.CV])

Visual as well as genetic biometrics are routinely employed to identify
species and individuals in biological applications. However, no attempts have
been made in this domain to computationally enhance visual classification of
rare classes with little image data via genetics. In this paper, we thus
propose aligned visual-genetic inference spaces with the aim to implicitly
encode cross-domain associations for improved performance. We demonstrate for
the first time that such alignment can be achieved via deep embedding models
and that the …

applications arxiv biometrics classification data genetics identify image inference paper