dc.contributor.author | Lahtinen, Tuomo | |
dc.contributor.author | Turtiainen, Hannu | |
dc.contributor.author | Costin, Andrei | |
dc.date.accessioned | 2021-07-28T10:23:17Z | |
dc.date.available | 2021-07-28T10:23:17Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Lahtinen, T., Turtiainen, H., & Costin, A. (2021). BRIMA : Low-Overhead Browser-Only Image Annotation Tool. In <i>ICIP 2021 : Proceedings of the 28th IEEE International Conference on Image Processing</i> (pp. 2633-2637). IEEE. Proceedings : International Conference on Image Processing. <a href="https://doi.org/10.1109/icip42928.2021.9506683" target="_blank">https://doi.org/10.1109/icip42928.2021.9506683</a> | |
dc.identifier.other | CONVID_99027000 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/77230 | |
dc.description.abstract | Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence fields. At the same time, it is well-known and acknowledged by the research community that the image annotation process is challenging, time-consuming and hard to scale. Therefore, the researchers and practitioners are always seeking ways to perform the annotations easier, faster, and at higher quality. Even though several widely used tools exist and the tools’ landscape evolved considerably, most of the tools still require intricate technical setups and high levels of technical savviness from its operators and crowdsource contributors.In order to address such challenges, we develop and present BRIMA – a flexible and open-source browser extension that allows BRowser-only IMage Annotation at considerably lower overheads. Once added to the browser, it instantly allows the user to annotate images easily and efficiently directly from the browser without any installation or setup on the client-side. It also features cross-browser and cross-platform functionality thus presenting itself as a neat tool for researchers within the Computer Vision, Artificial Intelligence, and privacy-related fields. | en |
dc.format.extent | 3926 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.relation.ispartof | ICIP 2021 : Proceedings of the 28th IEEE International Conference on Image Processing | |
dc.relation.ispartofseries | Proceedings : International Conference on Image Processing | |
dc.rights | In Copyright | |
dc.subject.other | image annotation | |
dc.subject.other | annotation tool | |
dc.subject.other | crowdsource annotation | |
dc.subject.other | image dataset generation | |
dc.subject.other | COCO | |
dc.title | BRIMA : Low-Overhead Browser-Only Image Annotation Tool | |
dc.type | conference paper | |
dc.identifier.urn | URN:NBN:fi:jyu-202107284401 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.relation.isbn | 978-1-6654-3102-6 | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 2633-2637 | |
dc.relation.issn | 1522-4880 | |
dc.type.version | draft | |
dc.rights.copyright | © 2021 IEEE | |
dc.rights.accesslevel | openAccess | fi |
dc.type.publication | conferenceObject | |
dc.relation.conference | IEEE International Conference on Image Processing | |
dc.subject.yso | annotointi | |
dc.subject.yso | hahmontunnistus (tietotekniikka) | |
dc.subject.yso | konenäkö | |
dc.subject.yso | selaimet | |
dc.subject.yso | kuvat | |
dc.subject.yso | joukkoistaminen | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p24094 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p8266 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2618 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p8440 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p1149 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p25552 | |
dc.rights.url | http://rightsstatements.org/page/InC/1.0/?language=en | |
dc.relation.doi | 10.1109/icip42928.2021.9506683 | |
jyx.fundinginformation | Authors acknowledge grants of computer capacity from the Finnish Grid and Cloud Infrastructure (FGCI) (persistent identifier urn:nbn:fi:research-infras-2016072533). Part of this research was kindly supported by the “Decision of the Research Dean on research funding within the Faculty (17.06.2020)” (the grant from Faculty of Information was facilitated and managed by Dr. Andrei Costin). Hannu Turtiainen also thanks The Finnish Cultural Foundation / Suomen Kulttuurirahasto (https://skr.fi/en) for supporting his Ph.D. research (grant decision 00211119), and The Faculty of Information Technology, in particular Prof. Timo Hamäläinen, for partly supporting his Ph.D. supervission at JYU in 2021. | |
dc.type.okm | A4 | |