Deep learning tools for the measurement of animal behavior in neuroscience
By Mackenzie W. Mathis, Alexander Mathis. Current Opinion in Neurobiology, 2019
397 citations recorded by the source corpus.
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capturing the postures of animals-pose estimation - has been rapidly advancing with new deep learning methods. While challenges still remain, we envision that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience.
Subfields: Cell Biology, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/4453e2836e271dfda8b863099a27df1e33bdd506
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cell Biology
- Erica Schmidt
- Maithra Raghu
- E. Davis
- Robert M. Kanko
- E. Laende
- K. Deluzio
- W. Selbie
- Alexander Mathis
In Computer Vision and Pattern Recognition
- Sara Beery
- Erica Schmidt
- Maithra Raghu
- Benjamin Kellenberger
- Grant Van Horn
- R. Kays
- Blair R. Costelloe
- Tanya Y. Berger-Wolf
Citations in the corpus
- Concurrent assessment of gait kinematics using marker-based and markerless motion capture (2020, positive): “…(Theia Markerless Inc., Kingston, ON, Canada) is a deep learning algorithm-based approach to markerless motion capture which uses deep convolutional neural networks for feature recognition (humans and human features) within 2D camera views (Kanko et al., 2020a, 2020b; Mathis and Mathis, 2020).”
- A Survey of Deep Learning for Scientific Discovery (2020, methodology): “An example is given by [146, 147], with associated code http://www.”
- Perspectives in machine learning for wildlife conservation (2021, methodology): “For pose estimation, marker-less methods based on DL have tremendously improved over the last years and already impacted biology (109).”