Segmenter: Transformer for Semantic Segmentation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Image segmentation is often ambiguous at the level of individual image patches and requires contextual information to reach label consensus. In this paper we introduce Segmenter, a transformer model for semantic segmentation.
Robin Strudel +3 more
semanticscholar +6 more sources
The Terms Segment and Segmentation in Geology [PDF]
Science, 1913 n ...
Geo. I. Adams
openalex +5 more sources
Questing in city promotion on the example of the city of Częstochowa [PDF]
Innovative Marketing, 2018 Gamification, storytelling and questing are the latest discoveries of marketing that are used for customers’ attraction. The implementation of new methods for promoting the city of Częstochowa is a vital aspect in tourism development.
Agnieszka Widawska-Stanisz
doaj +2 more sources
Specifics of the use of text categories in the texts of court decisions (based on the decision of the Supreme Court of Great Britain in the case «Perry v Raleys Solicitors») [PDF]
Актуальные проблемы филологии и педагогической лингвистики, 2020 The article discusses the specifics of the implementation of textual categories of connectedness, informativeness, segmentation, retrospection and modality in the texts of court decisions (based on the decision of the Supreme Сourt of Great Britain in ...
Suetina Olesya G.
doaj +1 more source
Masked-attention Mask Transformer for Universal Image Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 Image segmentation groups pixels with different semantics, e.g., category or instance membership. Each choice of semantics defines a task. While only the semantics of each task differ, current research focuses on designing spe-cialized architectures for ...
Bowen Cheng +4 more
semanticscholar +1 more source
Cerebral Microbleed Automatic Detection System Based on the “Deep Learning”
Frontiers in Medicine, 2022 ObjectiveTo validate the reliability and efficiency of clinical diagnosis in practice based on a well-established system for the automatic segmentation of cerebral microbleeds (CMBs).MethodThis is a retrospective study based on Magnetic Resonance Imaging-
Pingping Fan +21 more
doaj +1 more source
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation [PDF]
Computer Vision and Pattern Recognition, 2016 Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images. This, however, renders data unnecessarily voluminous and causes issues. In
C. Qi, Hao Su, Kaichun Mo, L. Guibas
semanticscholar +1 more source
Medical image segmentation using modified active contour method [PDF]
Serbian Journal of Electrical Engineering, 2017 Image data is of major practical importance in medical informatics. Accurate segmentation of medical images largely determines the final result of image analysis, which provides significant information for 3D visualization, surgical planning and
Voronin Viacheslav +4 more
doaj +1 more source
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit.
Liang-Chieh Chen +4 more
semanticscholar +1 more source
Dual Attention Network for Scene Segmentation [PDF]
Computer Vision and Pattern Recognition, 2018 In this paper, we address the scene segmentation task by capturing rich contextual dependencies based on the self-attention mechanism. Unlike previous works that capture contexts by multi-scale features fusion, we propose a Dual Attention Networks (DANet)
J. Fu +4 more
semanticscholar +1 more source