1 to 10 of 15 Results
Aug 22, 2024
Chan, Hoi Hang; Putra, Prasetia; Schupp, Harald; Köchling, Johanna; Straßheim, Jana; Renner, Britta; Schroeder, Julia; Pearse, William D; Nakagawa, Shinichi; Burke, Terry; Griesser, Michael; Meltzer, Andrea; Lubrano, Saverio; Kano, Fumihiro, 2024, "Sample Dataset for YOLO-Behaviour: A simple, flexible framework to automatically quantify animal behaviours from videos", https://doi.org/10.17617/3.EZNKYV, Edmond, V1
Sample dataset and weights for YOLO-Behaviour framework. Required to run demo code in the documentation. Also provided bounding box datasets for 4 case studies in YOLO format. The human dataset is not included due to privacy concerns. Code: https://github.com/alexhang212/YOLO_Beh... |
Jul 26, 2024
Schaefer-Zimmermann, Julian; Demartsev, Vlad; Averly, Baptiste; Dhanjal-Adams, Kiran; Duteil, Mathieu; Gall, Gabriella; Faiß, Marius; Johnson-Ulrich, Lily; Stowell, Dan; Manser, Marta; Roch, Marie; Strandburg-Peshkin, Ariana, 2024, "Pretrained models for animal2vec and MeerKAT: A self-supervised transformer for rare-event raw audio input and a large-scale reference dataset for bioacoustics", https://doi.org/10.17617/3.ETPUKU, Edmond, V1
Model weights for animal2vec Please find the accompanying code at our official repository: github.com/livingingroups/animal2vec Here you find the model weights for the pretrained and the finetuned animal2vec model using the MeerKAT dataset. For more information on how to use this... |
Schaefer-Zimmermann, Julian; Demartsev, Vlad; Averly, Baptiste; Dhanjal-Adams, Kiran; Duteil, Mathieu; Gall, Gabriella; Faiß, Marius; Johnson-Ulrich, Lily; Stowell, Dan; Manser, Marta; Roch, Marie; Strandburg-Peshkin, Ariana, 2024, "MeerKAT: Meerkat Kalahari Audio Transcripts", https://doi.org/10.17617/3.0J0DYB, Edmond, V1
A large-scale reference dataset for bioacoustics Please find the accompanying code at our official repository: github.com/livingingroups/animal2vec [Optional ]You can find the animal2vec model weights using the MeerKAT dataset here. MeerKAT is a 1068h large-scale dataset containi... |
Jun 13, 2024
Chimento, Michael; Chan, Hoi Hang; Aplin, Lucy; Kano, Fumihiro, 2024, "Additional dataset for: Peering into the world of wild passerines with 3D-SOCS: synchronized video capture for posture estimation", https://doi.org/10.17617/3.ZQMOJ3, Edmond, V1
This dataset includes sample data to reproduce the 3D-SOCS pipeline, as well as an annotated dataset and trained model weights for object detection and 2D keypoint estimation for Great tits and Blue tits. For more details, code and implementation of the pipeline, we refer to: htt... |
May 28, 2024
Dang, Truong Ka My, 2023, "NeuroQuantify Dataset", https://doi.org/10.17617/3.UIBMJX, Edmond, V3
The segmentation of cells and neurites in microscopy images of neuronal networks provides valuable quantitative information about neuron growth and neuronal differentiation, including the number of cells, neurites, neurite length and neurite orientation. This information is essen... |
May 7, 2024
naik, Hemal; Chan, Alex Hoi Hang; Yang, Junran; Delacoux, Mathilde; Couzin, D. Iain; Kano, Fumihiro; Nagy, Mate, 2023, "3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture", https://doi.org/10.17617/3.HPBBC7, Edmond, V6
The 3DPOP dataset is a large scale 2D to 3D posture, identity and trajectory dataset for freely moving pigeons. We use marker-based motion tracking to first track precise head and body position and orientation for multiple individuals, then propagated custom keypoints based on th... |
Mar 26, 2024
Awad, Sherine; Valleriani, Angelo; Chiarugi, Davide, 2024, "A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length.", https://doi.org/10.17617/3.H7OPIB, Edmond, V1
Ribofilio is a software package that estimates the drop-off rate of ribosomes. It is a python package that takes as a required input the reference genome and the footprint. If the mRNA reads are available, this can be used as an optional parameter for normalization. The tool uses... |
Jan 3, 2024
Waldmann, Urs; Chan, Hoi Hang Alex; Naik, Hemal; Nagy, Mate; Couzin, Iain D.; Deussen, Oliver; Goldluecke, Bastian; Kano, Fumihiro, 2024, "Wild-MuPPET - Multi-view posture dataset of foraging pigeons in the wild", https://doi.org/10.17617/3.ENDMTI, Edmond, V1
Wild-MuPPET is a multi-view posture dataset of foraging pigeons outdoors, with 500 frames of 3D-ground truth and 2000 frames of 2D-ground truth of 9 keypoints. Paper: https://doi.org/10.48550/arXiv.2308.15316 Git repository: https://github.com/alexhang212/3D-MuPPET |
Fortmann-Grote, Carsten; Gericke, Beate Constanze; Werth, Sören; Degner, Finn; Hüttmann, Tom, 2023, "Supplementary Material for "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25"", https://doi.org/10.17617/3.MCK0KK, Edmond, V1
This upload contains all raw data, trained tensorflow models, and python code used for training and validation of deep learning image segmentation as described in the forthcoming paper "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for... |
Sep 21, 2023
Shiu, Philip; Spiller, Nico, 2023, "Drosophila Brain Model", https://doi.org/10.17617/3.CZODIW, Edmond, V3
A computational model of the Drosophila brain (bioRxiv, Github) |
