ON THE ISSUE OF DEVELOPING A DATA ANNOTATION SYSTEM FOR COMPUTER VISION TASKS

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Contacts

Olesya Leonidovna Nizhnikova
Research Engineer, Federal State Budget Scientific Institution "Institute of Artificial Intelligence Problems".
283048, 118 b Artyoma str., Donetsk.
Research interests: computer vision, machine learning, neural networks.

Maxim Vitalievich Blizno
Junior Researcher, Federal State Budget Scientific Institution "Institute of Artificial Intelligence Problems".
283048, 118 b Artyoma str., Donetsk.
Research interests: computer vision, machine learning, neural networks.

Renat Saitovich Khakimov
Junior Researcher, Federal State Budget Scientific Institution "Institute of Artificial Intelligence Problems".
283048, 118 b Artyoma str., Donetsk.
Research interests: computer vision, machine learning, neural networks.

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UDC 004.93/004.932
DOI 10.24412/2413-7383-2024-3-70-79
Language: Russian
Annotation: The article provides an analytical overview of software solutions for annotating data in order to highlight their functionality, identify advantages and disadvantages that should be taken into account when creating your own annotator.
Keywords: data annotation system, annotator, data markup.

List of literature:
1. Label Studio Enterprise [Electronic resource]. Access mode: https://labelstud.io / (date of access: 03/21/2024).
2. LabeIImg [Electronic resource]. Access mode: https:// github.com/HumanSignal/labelImg (date of access: 03/28/2024).
3. CVAT [Electronic resource]. Access mode: https://github.com/cvat-ai/cvat (date of access: 02/29/2024).
4. Fifty-One [Electronic resource]. Access mode: https://voxel51.com/fiftyone-teams / (date of access: 04/29/2024).
5. ImageTagger [Electronic resource]. Access mode: https://github.com/bit-bots/imagetagger (date of application: 04/29/2024).
6. COCO Annotator [Electronic resource]. Access mode: https://github.com/jsbroks/coco-annotator (date of access: 04/29/2024).
7. V7 Labs [Electronic resource]. Access mode: https://www.v7labs.com / (date of access: 04/29/2024).
8. Labelbox [Electronic resource]. Access mode: https://labelbox.com / (date of access: 04/29/2024).
9. SuperAnnotate [Electronic resource]. Access mode: https://www.superannotate.com / (date of access: 04/29/2024).
10. Supervisely [Electronic resource]. Access mode: https://supervisely.com / (date of access: 04/29/2024).
11. RectLabel [Electronic resource]. Access mode: https://rectlabel.com / (date of access: 04/29/2024).
12. Deepen [Electronic resource]. Access mode: https://www.deepen.ai / (date of access: 04/29/2024).
13. Alegion [Electronic resource]. Access mode: https://alegion.com / (date of access: 04/29/2024).
14. Hasty.ai [Electronic resource]. Access mode: https://hasty.cloudfactory.com / (date of access: 04/29/2024).
15. Diffgram [Electronic resource]. Access mode: https://www.diffgram.com/#use_cases (date of application: 04/29/2024).
16. Akimov, A. A. Preliminary data processing for machine learning [Text] / A. A. Akimov, D. R. Valitov, A. I. Kubryak // Scientific Review. Technical sciences. 2022. No. 2. pp. 26-31.
17. Shlyapnikov, V. M. Development of a prototype of an image annotation system for computer vision models [Text] / V. M. Shlyapnikov // Scientific interdisciplinary research. 2020. No. 8-1. pp. 107-114.

Release: 3(34)'2024
Chapter: SYSTEM ANALYSIS, CONTROL AND INFORMATION PROCESSING, STATISTICS
How to quote: Khakimov R.S. Nizhnikova O.L. Blizno M.V. ON THE ISSUE OF DEVELOPING A DATA ANNOTATION SYSTEM FOR COMPUTER VISION TASKS [Text] / R.S. Khakimov, O.L. Nizhnikova, M.V. Blizno // Problems of artificial intelligence. - 2024. № 3 (34). - P. 70-79. - http://paijournal.guiaidn.ru/ru/2024/3(34)-8.html

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