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Awesome Deep Ecology Awesome

A curated list of deep learning resources for computer vision, inspired by awesome-deep-vision and awesome-computer-vision.

We are looking for additional maintainers! Let me know (pcg19 at duke) if interested.

An introduction to Deep Learning for Ecology with some neural networks you can run in the cloud to get a more intuitive understanding of deep learning, as well as suggestions for papers, videos, and quick resources, can be found here.





  • Deep learning for benthic fauna identification. OCEANS 2016 MTS/IEEE Monterey, OCE 2016.
    • Marburg, A., & Bigham, K. (2016).
    • doi:10.1109/OCEANS.2016.7761146
  • Right whale recognition using convolutional neural networks.

Camera Traps

Aerial Imagery

  • Multi-modal survey of Adélie penguin mega-colonies reveals the Danger Islands as a seabird hotspot
    • Alex Borowicz, Philip McDowall, Casey Youngflesh, Thomas Sayre-McCord, Gemma Clucas, Rachael Herman, Steven Forrest, Melissa Rider, Mathew Schwaller, Tom Hart, Stéphanie Jenouvrier, Michael J. Polito, Hanumant Singh & Heather J. Lynch
  • Detecting Wildlife in Unmanned Aerial Systems Imagery Using Convolutional Neural Networks Trained with an Automated Feedback Loop
    • Bowley, C., Mattingly, M., Barnas, A., Ellis-Felege, S., & Desell, T. (2018).
    • doi:10.1007/978-3-319-93698-7_6
  • A comparison of deep learning and citizen science techniques for counting wildlife in aerial survey images



  • Fast accurate fish detection and recognition of underwater images with Fast R-CNN
  • Bat detective—Deep learning tools for bat acoustic signal detection


Semantic Segmentation

Pose Estimation

Other Topics



Further Reading


Please feel free to pull requests to add papers.


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