Release by AlexEMG · Pull Request #2602 · DeepLabCut/DeepLabCut
@@ -1,5 +1,5 @@
DeepLabCut (www.deeplabcut.org) was initially developed by
Alexander & Mackenzie Mathis in collaboration with Matthias Bethge.
Alexander & Mackenzie Mathis in collaboration with Matthias Bethge.
It is actively developed by Alexander & Mackenzie Mathis (steering council and owners).
DeepLabCut is an open-source tool and has benefited from suggestions and edits by many Expand Down Expand Up @@ -82,23 +82,23 @@ T Nath, https://github.com/meet10may
Preprint: Multi-animal pose estimation and tracking with DeepLabCut J Lauer, M Zhou, S Ye, W Menegas, S Schneider, T Nath, MM Rahman, V Di Santo, J Lauer, M Zhou, S Ye, W Menegas, S Schneider, T Nath, MM Rahman, V Di Santo, D Soberanes, G Feng, VN Murthy, G Lauder, C Dulac, M Mathis, A Mathis (2021). https://www.biorxiv.org/content/10.1101/2021.04.30.442096v1
Publication: Publication: Multi-animal pose estimation, identification and tracking with DeepLabCut Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M.M., Di Santo, V., Soberanes, D., Feng, G., Murthy, V.N., Lauder, G.V., Dulac, C., Mathis, M.W., & Mathis, A. (2022). Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M.M., Di Santo, V., Soberanes, D., Feng, G., Murthy, V.N., Lauder, G.V., Dulac, C., Mathis, M.W., & Mathis, A. (2022). Nature Methods, 19, 496 - 504.
Conceptualization was done by A.M. and M.W.M. Formal analysis and code were done by J.L., A.M. and M.W.M. New deep architectures were designed by M.Z., S.Y. and A.M. GUIs were done by J.L., M.W.M. and T.N. Benchmark was set by S.S., M.W.M., A.M. and J.L. Marmoset data were gathered by W.M. and G.F. Conceptualization was done by A.M. and M.W.M. Formal analysis and code were done by J.L., A.M. and M.W.M. New deep architectures were designed by M.Z., S.Y. and A.M. GUIs were done by J.L., M.W.M. and T.N. Benchmark was set by S.S., M.W.M., A.M. and J.L. Marmoset data were gathered by W.M. and G.F. Marmoset behavioral analysis was carried out by W.M. Parenting data were gathered by M.M.R., A.M. and C.D. Tri-mouse data were gathered by D.S., A.M. and V.N.M. Fish data were gathered by V.D.S. and G.L. The article was written by A.M., M.W.M. and J.L. with input from all authors. Tri-mouse data were gathered by D.S., A.M. and V.N.M. Fish data were gathered by V.D.S. and G.L. The article was written by A.M., M.W.M. and J.L. with input from all authors. M.W.M. and A.M. co-supervised the project.
############################################################################################################ Expand All @@ -110,6 +110,11 @@ J Lauer, jessy@deeplabcut.org | https://github.com/jeylau N Poulsen, neils.poulsen@epfl.ch | https://github.com/n-poulsen S Ye, https://github.com/yeshaokai
Preprint: Ye, S., Filippova, A., Lauer, J., Vidal, M., Schneider, S., Qiu, T., Mathis, A., & Mathis, M.W. (2022). Preprint: Ye, S., Filippova, A., Lauer, J., Vidal, M., Schneider, S., Qiu, T., Mathis, A., & Mathis, M.W. (2022). SuperAnimal pretrained pose estimation models for behavioral analysis. https://arxiv.org/abs/2203.07436
############################################################################################################ DeepLabCut 3.0+ additions: staty tuned, but includes BUCTD!
DeepLabCut is an open-source tool and has benefited from suggestions and edits by many Expand Down Expand Up @@ -82,23 +82,23 @@ T Nath, https://github.com/meet10may
Preprint: Multi-animal pose estimation and tracking with DeepLabCut J Lauer, M Zhou, S Ye, W Menegas, S Schneider, T Nath, MM Rahman, V Di Santo, J Lauer, M Zhou, S Ye, W Menegas, S Schneider, T Nath, MM Rahman, V Di Santo, D Soberanes, G Feng, VN Murthy, G Lauder, C Dulac, M Mathis, A Mathis (2021). https://www.biorxiv.org/content/10.1101/2021.04.30.442096v1
Publication: Publication: Multi-animal pose estimation, identification and tracking with DeepLabCut Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M.M., Di Santo, V., Soberanes, D., Feng, G., Murthy, V.N., Lauder, G.V., Dulac, C., Mathis, M.W., & Mathis, A. (2022). Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M.M., Di Santo, V., Soberanes, D., Feng, G., Murthy, V.N., Lauder, G.V., Dulac, C., Mathis, M.W., & Mathis, A. (2022). Nature Methods, 19, 496 - 504.
Conceptualization was done by A.M. and M.W.M. Formal analysis and code were done by J.L., A.M. and M.W.M. New deep architectures were designed by M.Z., S.Y. and A.M. GUIs were done by J.L., M.W.M. and T.N. Benchmark was set by S.S., M.W.M., A.M. and J.L. Marmoset data were gathered by W.M. and G.F. Conceptualization was done by A.M. and M.W.M. Formal analysis and code were done by J.L., A.M. and M.W.M. New deep architectures were designed by M.Z., S.Y. and A.M. GUIs were done by J.L., M.W.M. and T.N. Benchmark was set by S.S., M.W.M., A.M. and J.L. Marmoset data were gathered by W.M. and G.F. Marmoset behavioral analysis was carried out by W.M. Parenting data were gathered by M.M.R., A.M. and C.D. Tri-mouse data were gathered by D.S., A.M. and V.N.M. Fish data were gathered by V.D.S. and G.L. The article was written by A.M., M.W.M. and J.L. with input from all authors. Tri-mouse data were gathered by D.S., A.M. and V.N.M. Fish data were gathered by V.D.S. and G.L. The article was written by A.M., M.W.M. and J.L. with input from all authors. M.W.M. and A.M. co-supervised the project.
############################################################################################################ Expand All @@ -110,6 +110,11 @@ J Lauer, jessy@deeplabcut.org | https://github.com/jeylau N Poulsen, neils.poulsen@epfl.ch | https://github.com/n-poulsen S Ye, https://github.com/yeshaokai
Preprint: Ye, S., Filippova, A., Lauer, J., Vidal, M., Schneider, S., Qiu, T., Mathis, A., & Mathis, M.W. (2022). Preprint: Ye, S., Filippova, A., Lauer, J., Vidal, M., Schneider, S., Qiu, T., Mathis, A., & Mathis, M.W. (2022). SuperAnimal pretrained pose estimation models for behavioral analysis. https://arxiv.org/abs/2203.07436
############################################################################################################ DeepLabCut 3.0+ additions: staty tuned, but includes BUCTD!