Results 11 to 20 of about 5,849,321 (239)
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition [PDF]
International Conference on Pattern Recognition, 2022 While the Transformer architecture has become ubiquitous in the machine learning field, its adaptation to 3D shape recognition is non-trivial. Due to its quadratic computational complexity, the self-attention operator quickly becomes inefficient as the ...
Axel Berg, M. Oskarsson, M. O'Connor
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PolyNet: Polynomial Neural Network for 3D Shape Recognition with PolyShape Representation [PDF]
International Conference on 3D Vision, 2021 3D shape representation and its processing have substantial effects on 3D shape recognition. The polygon mesh as a 3D shape representation has many advantages in computer graphics and geometry processing.
Mohsen Yavartanoo +4 more
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Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views [PDF]
IEEE International Conference on Computer Vision, 2021 In this paper, we focus on recognizing 3D shapes from arbitrary views, i.e., arbitrary numbers and positions of viewpoints. It is a challenging and realistic setting for view-based 3D shape recognition.
Xin Wei +4 more
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MVTN: Multi-View Transformation Network for 3D Shape Recognition [PDF]
IEEE International Conference on Computer Vision, 2020 Multi-view projection methods have demonstrated their ability to reach state-of-the-art performance on 3D shape recognition. Those methods learn different ways to aggregate information from multiple views.
Abdullah Hamdi +4 more
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IET Radar, Sonar & Navigation, 2021 The radar cross section (RCS) is an important parameter that reflects the scattering characteristics of radar targets. Based on the monostatic radar RCS time series' statistical features by sliding window segmentation, a novel sliding window‐statistical ...
Lv Ye +5 more
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Non-gaussian shape recognition [PDF]
Journal of Cosmology and Astroparticle Physics, 2013 37 pages, 7 figures, 5 tables.
Byun, Joyce, Bean, Rachel
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Mathematics, 2021 Rigid shapes should be naturally compared up to rigid motion or isometry, which preserves all inter-point distances. The same rigid shape can be often represented by noisy point clouds of different sizes.
Yury Elkin, Vitaliy Kurlin
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TriangleConv: A Deep Point Convolutional Network for Recognizing Building Shapes in Map Space
ISPRS International Journal of Geo-Information, 2021 The classification and recognition of the shapes of buildings in map space play an important role in spatial cognition, cartographic generalization, and map updating.
Chun Liu +5 more
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Remote Sensing, 2022 Remote sensing target recognition has always been an important topic of image analysis, which has significant practical value in computer vision. However, remote sensing targets may be largely occluded by obstacles due to the long acquisition distance ...
Zekun Li, Baolong Guo, Fanjie Meng
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Shape descriptors for mode-shape recognition and model updating [PDF]
, 2009 The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques,
Mares, C, Mottershead, JE, Wang, W
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