Can AI Help Us Identify Animals?

MindxL@7411 December 3, 2019 5:21 pm

Thanks to the University of Minnesota for sponsoring this video! http://twin-cities.umn.edu/

New technology has revolutionized how we study wild animals, but it has also bogged down scientists with data…luckily, there’s an *intelligent* solution.

Thanks also to our Patreon patrons https://www.patreon.com/MinuteEarth and our YouTube members.
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To learn more, start your googling with these keywords:
Deep learning: a subset of machine learning in artificial intelligence that can learning from data that is unstructured or unlabeled
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If you liked this week’s video, you might also like:
Take a look at the Snapshot Serengeti colletion and try your hand at classifying species, counting animals, and determining behaviors: https://www.zooniverse.org/projects/zooniverse/snapshot-serengeti

Learn about the whale shark project and report your sightings: https://www.whaleshark.org/

Explore underwater recordings of humpback whales and make your own discoveries: https://patternradio.withgoogle.com/
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Credits (and Twitter handles):
Script Writer, Editor, Video Director and Narrator: Kate Yoshida (@KateYoshida)
Video Illustrator: Arcadi Garcia (@garirius)
With Contributions From: Henry Reich, Alex Reich, Ever Salazar, Peter Reich, David Goldenberg, Julián Gómez, Sarah Berman
Music by: Nathaniel Schroeder: http://www.soundcloud.com/drschroeder

Image Credits: All the photos of the savannah by the SnapshotSerengeti Project
https://snapshotserengeti.org

Sogod Bay Whale Shark video by Miguel Hilario

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References:

Duporge I, Isupova O, and Reece S (2019, April 4) Using Satellite Imagery and Machine Learning to Detect and Monitor Elephants. https://blog.hexagongeospatial.com/using-satellite-imagery-and-machine-learning-to-detect-and-monitor-elephants/

Norouzzadeh MS, Nguyen A, Kosmala M, Swanson A, Palmer MS, Packer C, and Clune J (2018). Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. Proceedings of the National Academy of Sciences of the United States of America 115 (25): E5716-E5725. https://dash.harvard.edu/bitstream/handle/1/37298550/6016780.pdf?sequence=1

Packer C, personal communication (2019, September 12).

Swanson AB, Kosmala M, Lintott CJ, Simpson RJ, Smith A, Packer C (2015) Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna. Scientific Data 2: 150026. https://www.nature.com/articles/sdata201526

Wildbook for Whale Sharks. https://www.whaleshark.org/

Category: National