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Merge branch 'master' of github.com:agentmorris/camera-trap-ml-survey
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agentmorris committed Dec 2, 2024
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* video-processor (MD workflow for security camera footage) ([github.com/evz/video-processor](https://github.com/evz/video-processor))
* Declas (client-side tool for running MD and classifiers) ([github.com/stangandaho/declas](https://github.com/stangandaho/declas))
* AI for Wildlife Monitoring (real-time alerts using 4G camera traps) ([github.com/ratsakatika/camera-traps])(https://github.com/ratsakatika/camera-traps/)
* Identifying snow depth in camera trap images ([github.com/catherine-m-breen/snowpoles](https://github.com/catherine-m-breen/snowpoles))

### Last updated < 2021

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* Fergus P, Chalmers C, Matthews N, Nixon S, Burger A, Hartley O, Sutherland C, Lambin X, Longmore S, Wich S. Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data. arXiv preprint arXiv:2411.14219. 2024 Nov 21.

* Darras KF, Balle M, Xu W, Yan Y, Zakka VG, Toledo-Hernández M, Sheng D, Lin W, Zhang B, Lan Z, Fupeng L. Eyes on nature: Embedded vision cameras for multidisciplinary biodiversity monitoring. BioRxiv. 2023 Jul 29:2023-07.

* Breen CM, Currier WR, Vuyovich C, Miao Z, Prugh LR. Snow depth extraction from time‐lapse imagery using a keypoint deep learning model. Water Resources Research. 2024 Jul;60(7):e2023WR036682.

* Gadot T, Istrate Ș, Kim H, Morris D, Beery S, Birch T, Ahumada J. To crop or not to crop: Comparing whole-image and cropped classification on a large dataset of camera trap images. IET Computer Vision, Nov 2024.

#### Papers from 2023

* Mounir R, Shahabaz A, Gula R, Theuerkauf J, Sarkar S. Towards automated ethogramming: Cognitively-inspired event segmentation for streaming wildlife video monitoring. International journal of computer vision. 2023 Sep;131(9):2267-97.
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