Skip navigation
Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/45936
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSorokina, V.-
dc.contributor.authorAblameyko, S.-
dc.date.accessioned2021-11-18T05:57:23Z-
dc.date.available2021-11-18T05:57:23Z-
dc.date.issued2021-
dc.identifier.citationSorokina, V. Extraction of Human Body Parts in Image Using Convolutional Neural Network and Attention Model / Sorokina V., Ablameyko S. // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 84–88.ru_RU
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/45936-
dc.description.abstractIn computer vision, human body parts extraction is a challenging task for many applications. In this work, we propose the algorithm to extract human body parts in images using the OpenPose system and attention model. The novelty of the proposed work is that algorithm is based on a convolutional neural network that uses a nonparametric representation to associate body parts with people in an image in combination with a new attention model that learns to focus on specific regions of different input features. The algorithm is a part of Smart Cropping system developed by us which aim is to cut the images and prepare e-commerce catalog.ru_RU
dc.language.isoenru_RU
dc.publisherUIIP NASBru_RU
dc.subjectматериалы конференцийru_RU
dc.subjectconference proceedingsru_RU
dc.subjecthuman body parts extractionru_RU
dc.subjectconvolutional neural networkru_RU
dc.subjectsmart croppingru_RU
dc.titleExtraction of Human Body Parts in Image Using Convolutional Neural Network and Attention Modelru_RU
dc.typeСтатьяru_RU
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)

Files in This Item:
File Description SizeFormat 
Sorokina_Extraction.pdf1.31 MBAdobe PDFView/Open
Show simple item record Google Scholar

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.