Seeing biodiversity: perspectives in machine learning for wildlife conservation

no code implementations • 25 Oct 2021 • Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W. Mathis, Frank van Langevelde, Tilo Burghardt, Roland Kays, Holger Klinck, Martin Wikelski, Iain D. Couzin, Grant van Horn, Margaret C. Crofoot, Charles V. Stewart, Tanya Berger-Wolf

Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging devices.

BIG-bench Machine Learning

AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild

1 code implementation • 24 Mar 2021 • Daniel Joska, Liam Clark, Naoya Muramatsu, Ricardo Jericevich, Fred Nicolls, Alexander Mathis, Mackenzie W. Mathis, Amir Patel

Animals are capable of extreme agility, yet understanding their complex dynamics, which have ecological, biomechanical and evolutionary implications, remains challenging.

3D Pose Estimation Animal Pose Estimation +1

Measuring and modeling the motor system with machine learning

no code implementations • 22 Mar 2021 • Sébastien B. Hausmann, Alessandro Marin Vargas, Alexander Mathis, Mackenzie W. Mathis

The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data.

BIG-bench Machine Learning Dimensionality Reduction +2

A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives

1 code implementation • 1 Sep 2020 • Alexander Mathis, Steffen Schneider, Jessy Lauer, Mackenzie W. Mathis

Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem.

Deep learning tools for the measurement of animal behavior in neuroscience

6 code implementations • 30 Sep 2019 • Mackenzie W. Mathis, Alexander Mathis

Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality.

Pose Estimation

Pretraining boosts out-of-domain robustness for pose estimation

2 code implementations • 24 Sep 2019 • Alexander Mathis, Thomas Biasi, Steffen Schneider, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis

Neural networks are highly effective tools for pose estimation.

Animal Pose Estimation Benchmarking +1

Markerless tracking of user-defined features with deep learning

1 code implementation • 9 Apr 2018 • Alexander Mathis, Pranav Mamidanna, Taiga Abe, Kevin M. Cury, Venkatesh N. Murthy, Mackenzie W. Mathis, Matthias Bethge

Quantifying behavior is crucial for many applications in neuroscience.

Animal Pose Estimation Transfer Learning