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ShareScore release 0.9.0
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2 results for “cartoon dataset”
Cartoon images dataset for total variation parameter learning
<p>This dataset contains test and training image data for results presented in:</p> <p>Bredies K., Chenchene E., Hosseini A. A hybrid proximal generalized conditional gradient method and application to total variation parameter learning. 2022. <a href="https://arxiv.org/abs/2211.00997">https://arxiv.org/abs/2211.00997</a></p> <p>Also, see the <a href="https://github.com/TraDE-OPT/TV-parameter-learning">GitHub repository</a> for the implementation.</p> <p>Training and test sets have been downloaded from <a href="https://pixabay.com/">Pixabay</a> with permission.</p> <p> </p>
ImageNet-Cartoon and ImageNet-Drawing: two domain shift datasets for ImageNet
<p>Benchmarking the robustness to distribution shifts traditionally relies on dataset collection which is typically laborious and expensive, in particular for datasets with a large number of classes like ImageNet. An exception to this procedure is ImageNet-C (Hendrycks & Dietterich, 2019), a dataset created by applying common real-world corruptions at different levels of intensity to the (clean) ImageNet images. Inspired by this work, we introduce ImageNet-Cartoon and ImageNet-Drawing, two datasets constructed by converting ImageNet images into cartoons and colored pencil drawings, using a GAN framework (Wang & Yu, 2020) and simple image processing (Lu et al., 2012), respectively.</p> <p>This repository contains ImageNet-Cartoon and ImageNet-Drawing. Checkout the <a href="https://github.com/oberman-lab/imagenet-shift">official GitHub Repo</a> for the code on how to reproduce the datasets.</p> <p>If you find this useful in your research, please consider citing:</p> <p> @inproceedings{imagenetshift,<br> title={ImageNet-Cartoon and ImageNet-Drawing: two domain shift datasets for ImageNet},<br> author={Tiago Salvador and Adam M. Oberman},<br> booktitle={ICML Workshop on Shift happens: Crowdsourcing metrics and test datasets beyond ImageNet.},<br> year={2022}<br> }</p>
ScienceDex guides
Understand access before you commit
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.