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AI for Conservation: Learning to track birds with radar

Authors:

Zezhou Cheng,

Subhransu Maji,

Daniel SheldonAuthors Info & Claims

XRDS: Crossroads, The ACM Magazine for Students, Volume 27, Issue 4

Pages 26 - 29

https://doi.org/10.1145/3466859

Published: 24 June 2021 Publication History

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Abstract

How deep neural networks can process millions of weather radar data points to help researchers monitor continental-scale bird migration.

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References

[1]

Rosenberg, K. V., et al. Decline of the North American avifauna. Science 366, 6461 (2019), 120–124.

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[2]

Lin, T. Y., et al. MistNet: Measuring historical bird migration in the US using archived weather radar data and convolutional neural networks. Methods in Ecology and Evolution 10 (2019), 1908–1922.

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[3]

Spiller, K. J., and Dettmers, R. Evidence for multiple drivers of aerial insectivore declines in North America. The Condor 121, 2 (2019), duz010.

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Ren, S., et al. Faster R-CNN: Towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence 39, 6 (2017), 1137–1149.

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Deng, J., et al. ImageNet: A large-scale hierarchical image database. In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR ‘09) . IEEE, 2009, 248–255.

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Cheng, Z., et al. Detecting and tracking communal bird roosts in weather radar data. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI ‘20) . 2020, 378–385.

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Index Terms

AI for Conservation: Learning to track birds with radar
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Machine learning
2. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval

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Published In

cover image XRDS: Crossroads, The ACM Magazine for Students

XRDS: Crossroads, The ACM Magazine for Students Volume 27, Issue 4

Computing and Sustainability

Summer 2021

59 pages

ISSN:1528-4972

EISSN:1528-4980

DOI:10.1145/3472736

Editor:
Karan Ahuja
Carnegie Mellon University

Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 June 2021

Published in XRDS Volume 27, Issue 4

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AI for conservation

learning to track birds with radar