Onboarding Papers

Below are some good papers for each project that will help you get a feel for what the project is about.

Acoustic Species ID

S. Kahl, M. Clapp, W. A. Hopping, H. Goëau, H. Glotin, R. Planqué, W.-P. Vellinga, and A. Joly, “Overview of birdclef 2020: Bird sound recognition in complex acoustic environments,” in CLEF 2020-Conference and Labs of the Evaluation Forum, vol. 2696, 2020. [ .pdf ]

J. Ayers, Y. Jandali, Y. J. Hwang, G. Steinberg, E. Joun, M. Tobler, I. Ingram, R. Kastner, and C. Schurgers, “Challenges in applying audio classification models to datasets containing crucial biodiversity information,” in 38th International Conference on Machine Learning, vol. 38, July 2021. [ arXiv | .pdf ]

S. Kahl, T. Denton, H. Klinck, H. Reers, F. Cherutich, H. Glotin, H. Goëau, W.-P. Vellinga, R. Planqué, and A. Joly, “Overview of birdclef 2023: Automated bird species identification in eastern africa,” Working Notes of CLEF, 2023. [ http ]

Baboons on the Move

R. LaLonde, D. Zhang, and M. Shah, “Clusternet: Detecting small objects in large scenes by exploiting spatio-temporal information,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4003–4012, 2018. [ DOI ]

C. L. Crutchfield, J. Sutton, A. Ngo, E. Zadorian, G. Hourany, D. Nelson, A. Wang, F. McHenry-Crutchfield, D. Forster, S. C. Strum, R. Kastner, and C. Schurgers, “Baboons on the move: Enhancing understanding of collective decision making through automated motion detection from aerial drone footage,” in 12th International Conference on Methods and Techniques in Behavioral Research and 6th Seminar on Behavioral Methods, vol. 1, pp. 33 – 39, October 2021. [ DOI | http ]

Q. Yin, Q. Hu, H. Liu, F. Zhang, Y. Wang, Z. Lin, W. An, and Y. Guo, “Detecting and tracking small and dense moving objects in satellite videos: A benchmark,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1–18, 2022. [ DOI ]

FishSense

P. Tueller, R. Maddukuri, P. Paxson, V. Suresh, A. Ashok, M. Bland, R. Wallace, J. Guerrero, B. Semmens, and R. Kastner, “Fishsense: Underwater rgbd imaging for fish measurement and classification,” in OCEANS 2021 MTS/IEEE SAN DIEGO, IEEE, September 2021. [ http ]

E. Wong, I. Humphrey, S. Switzer, C. Crutchfield, N. Hui, C. Schurgers, and R. Kastner, “Underwater depth calibration using a commercial depth camera,” 2022. [ DOI | http ]

Mangrove Monitoring

A. J. Hsu, E. Lo, J. Dorian, K. Qi, M. T. Costa, and B. G. Martinez, “Lessons on monitoring mangroves,” in UC San Diego: Aburto Lab, UC San Diego, 2019. [ http ]

D. Hicks, R. Kastner, C. Schurgers, A. Hsu, and O. Aburto, “Mangrove ecosystem detection using mixed-resolution imagery with a hybrid-convolutional neural network,” in Thirty-fourth Conference on Neural Information Processing Systems Workshop: Tackling Climate Change with Machine Learning, 2020. [ DOI | .pdf ]

Radio Telemetry Tracking

N. T. Hui, E. K. Lo, J. B. Moss, G. P. Gerber, M. E. Welch, R. Kastner, and C. Schurgers, “A more precise way to localize animals using drones,” Journal of Field Robotics, 2021. [ DOI | arXiv | http ]

Smartfin

P. Bresnahan, T. Cyronak, R. J. Brewin, A. Andersson, T. Wirth, T. Martz, T. Courtney, N. Hui, R. Kastner, A. Stern, T. McGrain, D. Reinicke, J. Richard, K. Hammond, and S. Waters, “A high-tech, low-cost, internet of things surfboard fin for coastal citizen science, outreach, and education,” Continental Shelf Research, vol. 242, p. 104748, 2022. [ DOI | http ]

N. Hui, “Smartfin current efforts.” GitHub, Sept. 2023. [ http ]

Research Support Group

“E4e hardware group.” [ http ]

“E4e hardware group – active tasks.” [ http ]

“E4e engineering support group.” [ http ]

Updated 2024-01-27T07:01:37