Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

2

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

2 results for “on-line recognition”

Learn how ShareScore rates datasets ↗
zenodo44/100

The ICDAR 2003 Informal Competition for the Recognition of On-line Words: The Unipen-ICROW-03 benchmark set - Version 0.0

<p>Proposal for an informal benchmark on word recognition. See for the related ImUnipen collection<br> of word images from on-line vectorial handwriting data:&nbsp;https://zenodo.org/record/1195059</p> <p>At the time (ICDAR 2003) there was not a lot of interest so the project was not pursued.</p> <p>Lambert Schomaker - February 2023</p> <p>_______________________________________________________________________________</p> <p>The ICDAR 2003 Informal Competition for the Recognition of On-line Words:<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;The Unipen-ICROW-03 benchmark set&nbsp;<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Version 0.0</p> <p>Lambert Schomaker / International Unipen Foundation</p> <p>The ICROW suite of test files for the recognition of isolated on-line<br> free-style (handprint, mixed and cursive) words has been<br> composed. Different tablets, nationalities and languages<br> are involved. Only the ASCII set is used within word labels.</p> <p>The set contains:</p> <p>&nbsp; &nbsp;13119 written words<br> &nbsp; &nbsp; &nbsp;884 unique lexical word entries<br> &nbsp; &nbsp; &nbsp; 72 writers&nbsp;</p> <p>Language: Dutch, English, Italian.<br> Nationalities: Dutch, Irish, Italian, + mixed</p> <p>The benchmark test is a good estimator for&nbsp;<br> &quot;walk-up&quot; recognition performance.</p> <p>[Note: some of the writers (NIC-Pc95*.dat set) are present in the<br> UNIPEN R01/V07 distribution, but the actual words are unseen&nbsp;<br> outside of the Int. Unipen Foundation.]</p> <p>Please note the Copyright notice in the&nbsp;<br> accompanying file &#39;Copyright&#39;</p> <p>Wed Jul 16 21:20:10 CEST 2003</p> <p>Lambert Schomaker</p> <p>---------------------------------------------------------------------------</p> <p>Instructions for the ICDAR 2003 informal competition for<br> the recognition of on-line words.</p> <p>1 - unpack the .tgz file<br> 2 - use the UNIPEN files as input for your recognizer.<br> 3 - report, for each writer, a file &lt;writer-id&gt;.res</p> <p>&nbsp; Example: do-my-recognizer &lt; NIC-Hi93b-marc.dat &gt; NIC-Hi93b-marc.res</p> <p>Format of the .res file.</p> <p>No XML for this moment: simplicity does it.</p> <p>We assume that the recognizer is able to produce a top-10 list<br> of likely words, sorted from most likely to least likely.<br> The output for each word is on a single line. The correct<br> target word is in the first column.</p> <p>&lt;targetword 1&gt; &lt;best word hyp.&gt; &lt;2nd-best word hyp.&gt; ... &lt;10th-best word hyp&gt;<br> &lt;targetword 2&gt; &lt;best word hyp.&gt; &lt;2nd-best word hyp.&gt; ... &lt;10th-best word hyp&gt;</p> <p>Example with two words:</p> <p>summertime &nbsp; slumbertime slipknot summertime somatome spumante simulative semitone schoolmate sermonette semimature<br> Aberdeen &nbsp; &nbsp; Adamson Aberdeen Addison Armageddon Abyssinian Araban Albanian Alabamian Abraham Adelaide</p> <p><br> 4 - pack the &nbsp;*.res files in a .tgz or .zip file and send them<br> &nbsp; &nbsp; to schomaker@ai.rug.nl<br> &nbsp; &nbsp; All *.dat files need to be processed.</p> <p>LS.<br> &nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2003View details →
dryad28/100

Data from: Self-recognition in crickets via on-line processing

Open the record for dataset details and reuse information.

publicOct 2015View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record