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23
datasets available to search
ShareScore release 0.9.0
Dataset results
23 results for “Generative Adversarial Network”
STCGAN: a novel Cycle-Consistent Generative Adversarial Network for Spatial Transcriptomics Cellular Deconvolution
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Image Synthesis with a Convolutional Capsule Generative Adversarial Network- Prepared Data
<p>A set of prepared datasets for running experiments to replicate paper (see below).</p> <p>List of data:</p> <p>Training capspix2pix:</p> <ul> <li>crops256.zip - folder containing 256x256 crops from the original dataset for training capspix2pix. Images are in the "train/original" folder, and labels are in the "train/mask" folder.</li> <li>syn256_x_data_val.npy + syn256_y_data_val.npy + syn256_y_points_data_val.npy (images + labels + centrelines) - validation synthetic dataset, used while training capspix2pix for plotting</li> </ul> <p>Training u-net:</p> <ul> <li>capspix2pix_AR_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from real labels</li> <li>capspix2pix_SSM_data_train.npy + capspix2pix_AR_mask_train.npy (images + labels) - data generated from a capspix2pix model from synthetic labels</li> <li>PBAM_SSM_data_train.npy + PBAM_SSM_mask_train.npy (images + labels) - data generated from PBAM (Physics-based model) for training u-net</li> <li>pix2pix_AR_data_train.npy + pix2pix_AR_mask_train.npy (images + labels) - data generated from a pix2pix model from real labels for training u-net</li> <li>pix2pix_SSM_data_train.npy + pix2pix_SSM_mask_train.npy (images + labels) - data generated from a pix2pix model from synthetic labels for training u-net</li> <li>real_data_data_train.npy + real_data_mask_train.npy (images + labels) - augmented real dataset for training u-net</li> </ul> <p>Testing u-net:</p> <ul> <li>org64_data_test.npy + org64_mask_test.npy (images + labels) - crops from original test dataset for testing u-net</li> </ul> <p>Interpolation:</p> <ul> <li>crops256_inter_data_train.npy + crops256_inter_mask_train.npy (images + labels) - example data for interpolation</li> </ul> <p><strong>Please cite the following paper when using this dataset:</strong></p> <p>Bass, C., Dai, T., Billot, B., Arulkumaran, K., Creswell, A., Clopath, C., De Paola, V., and Bharath, A. A., 2019. “Image synthesis with a convolutional capsule generative adversarial network,” <em>Medial Imaging with Deep Learning.</em></p> <p><strong>See Github page for further instructions:</strong></p> <p>https://github.com/CherBass/CapsPix2Pix</p> <p> </p>
Dataset of "Super-resolution generative adversarial networks of randomly seeded fields"
<p>Dataset of the article "Super-resolution generative adversarial networks of randomly seeded fields" (https://doi.org/10.1038/s42256-022-00572-7)</p> <p>The codes processing data here are on https://github.com/eaplab/RaSeedGAN</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 949085, NEXTFLOW).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.