Results 11 to 20 of about 14,780,830 (367)
Application of Improved KAZE Algorithm in Image Feature Extraction and Matching
IEEE Access, 2023 Intelligent navigation and recognition technology have continuously improved the field of image matching, so how to achieve more efficient and accurate feature matching is the key to image processing.
Peipei Zhang, Xin'e Yan
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Earth and Space Science, 2021 Precipitation anomaly grades are usually defined by the percentage anomaly (Pa) or probability distribution (Pd) methods. However, the difference between the two may lead to different estimates for the same events, creating difficulty in judging the ...
Yayu Ma +3 more
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Quantisation Scale-Spaces [PDF]
, 2021 To appear in A. Elmoataz, J. Fadili, Y. Queau, J. Rabin, L. Simon (Eds.): Scale Space and Variational Methods in Computer Vision.
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Occurrence frequency of subcritical Richardson numbers assessed by global high-resolution radiosonde and ERA5 reanalysis [PDF]
Atmospheric Chemistry and Physics, 2023 Kelvin–Helmholtz instability (KHI) is most likely to be the primary source for clear-air turbulence, which is of importance in pollution transfer and diffusion and aircraft safety. It is indicated by the critical value of the dimensionless Richardson (Ri)
J. Shao +6 more
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Intrinsic Image Transformation via Scale Space Decomposition [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 We introduce a new network structure for decomposing an image into its intrinsic albedo and shading. We treat it as an image-to-image transformation problem and explore the scale space of the input and output.
Lechao Cheng +2 more
semanticscholar +1 more source
The Active Segmentation Platform for Microscopic Image Classification and Segmentation
Brain Sciences, 2021 Image segmentation still represents an active area of research since no universal solution can be identified. Traditional image segmentation algorithms are problem-specific and limited in scope.
Sumit K. Vohra, Dimiter Prodanov
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Journal of Mathematical Imaging and Vision, 2001 We investigate the deep structure of a scale space image. We concentrate on scale space critical points—points with vanishing gradient with respect to both spatial and scale direction. We show that these points are always saddle points. They turn out to be extremely useful, since the iso-intensity manifolds through these points provide a scale space ...
Kuijper, Arjan +2 more
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ImageBind One Embedding Space to Bind Them All [PDF]
Computer Vision and Pattern Recognition, 2023 We present ImageBind, an approach to learn a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. We show that all combinations of paired data are not necessary to train such a joint embedding, and only ...
Rohit Girdhar +6 more
semanticscholar +1 more source
Large scale rank of Teichmuller space [PDF]
, 2014 Let X be quasi-isometric to either the mapping class group equipped with the word metric, or to Teichmuller space equipped with either the Teichmuller metric or the Weil-Petersson metric.
Eskin, Alex, Masur, Howard, Rafi, Kasra
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Interpreting large-scale redshift-space distortion measurements [PDF]
, 2011 The simplest theory describing large-scale redshift-space distortions (RSD), based on linear theory and distant galaxies, depends on the growth of cosmological structure, suggesting that strong tests of General Relativity can be constructed from galaxy ...
A. Raccanelli +81 more
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