Horizontal attention convolution layer for stereo matching

dc.authorid0000-0001-9877-5493en_US
dc.authorscopusid55200104100en_US
dc.contributor.authorEmlek A.
dc.contributor.authorPeker, Murat
dc.date.accessioned2022-04-21T05:40:01Z
dc.date.available2022-04-21T05:40:01Z
dc.date.issued2021en_US
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Mekatronik Mühendisliği Bölümüen_US
dc.description.abstractObtaining a disparity map with stereo matching is one of the most important research topics in areas such as image processing and computer vision. Disparity maps are frequently used by autonomous systems that need depth information of the environment. Recently, high accuracy disparity maps have been obtained with end-to-end deep learning. In this study, a horizontal attention-based convolution layer has been proposed in order to better extract the sequential information in the horizontal plane in the rectified stereo images in methods based on deep learning. The proposed structure has been applied to the DispNetC network, which has been widely used in the literature, and has increased the performance of the network. On the other hand, the proposed method have a very low effect on the network's runtime. The results obtained are shown on the Scene Flow dataset. The codes of the study are available at the following address: https://github.com/aemlek/HADN.en_US
dc.identifier.doi10.1109/SIU53274.2021.9478039en_US
dc.identifier.isbn978-166543649-6
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/1903
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPeker, Murat
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofSIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectConvolutional neural networks;en_US
dc.subjectDisparity mapen_US
dc.subjectStereo visionen_US
dc.titleHorizontal attention convolution layer for stereo matchingen_US
dc.title.alternativeStereo eşleştirme için yatay dikkatli evrişim katmanien_US
dc.typeConference Objecten_US

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