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Species Classification using Multimodal Heterogeneous Context

We present a species classification model that utilizes heterogeneous image contexts organized in a multimodal knowledge graph. The multimodal knowledge graph may include diverse forms of heterogeneous contexts that pertain to different modalities, such as numerical information for locations and time, categorical data for species/taxon IDs, and visual content such as images.

Authors: Vardaan Pahuja, Weidi Luo, Yu Gu, Cheng-Hao Tu, Hong-You Chen, Tanya Berger-Wolf, Charles Stewart, Song Gao, Wei-Lun Chao, Yu Su

GitHub Repo License: MIT

Acknowledgements​

This work has been funded by grants from the National Science Foundation, including the ICICLE AI Institute (OAC 2112606)