000 | 07054nam a22006615i 4500 | ||
---|---|---|---|
001 | 978-3-030-75549-2 | ||
003 | DE-He213 | ||
005 | 20240730175712.0 | ||
007 | cr nn 008mamaa | ||
008 | 210429s2021 sz | s |||| 0|eng d | ||
020 |
_a9783030755492 _9978-3-030-75549-2 |
||
024 | 7 |
_a10.1007/978-3-030-75549-2 _2doi |
|
050 | 4 | _aTA1634 | |
072 | 7 |
_aUYQV _2bicssc |
|
072 | 7 |
_aCOM016000 _2bisacsh |
|
072 | 7 |
_aUYQV _2thema |
|
082 | 0 | 4 |
_a006.37 _223 |
245 | 1 | 0 |
_aScale Space and Variational Methods in Computer Vision _h[electronic resource] : _b8th International Conference, SSVM 2021, Virtual Event, May 16-20, 2021, Proceedings / _cedited by Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
|
300 |
_aXIV, 580 p. 36 illus. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12679 |
|
505 | 0 | _aScale Space and Partial Differential Equations Methods -- Scale-covariant and Scale-invariant Gaussian Derivative Networks -- Quantisation Scale-Spaces -- Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations -- Nonlinear Spectral Processing of Shapes via Zero-homogeneous Flows -- Total-Variation Mode Decomposition -- Fast Morphological Dilation and Erosion for Grey Scale Images Using the Fourier Transform -- Diffusion, Pre-Smoothing and Gradient Descent -- Local Culprits of Shape Complexity -- Extension of Mathematical Morphology in Riemannian Spaces -- Flow, Motion and Registration -- Multiscale Registration -- Challenges for Optical Flow Estimates in Elastography -- An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation -- Low-rank Registration of Images Captured Under Unknown, Varying Lighting -- Towards Efficient Time Stepping for Numerical Shape Correspondence -- First Order Locally Orderless Registration -- Optimization Theory and Methods in Imaging -- First Order Geometric Multilevel Optimization For Discrete Tomography -- Bregman Proximal Gradient Algorithms for Deep Matrix Factorization -- Hessian Initialization Strategies for L-BFGS Solving Non-linear Inverse Problems -- Inverse Scale Space Iterations for Non-Convex Variational Problems Using Functional Lifting -- A Scaled and Adaptive FISTA Algorithm for Signal-dependent Sparse Image Super-resolution Problems -- Convergence Properties of a Randomized Primal-Dual Algorithm with Applications to Parallel MRI -- Machine Learning in Imaging -- Wasserstein Generative Models for Patch-based Texture Synthesis -- Sketched Learning for Image Denoising -- Translating Numerical Concepts for PDEs into Neural Architectures -- CLIP: Cheap Lipschitz Training of Neural Networks -- Variational Models for Signal Processing with Graph Neural Networks -- Synthetic Imagesas a Regularity Prior for Image Restoration Neural Networks -- Geometric Deformation on Objects: Unsupervised Image Manipulation via Conjugation -- Learning Local Regularization for Variational Image Restoration -- Segmentation and Labelling -- On the Correspondence between Replicator Dynamics and Assignment Flows -- Learning Linear Assignment Flows for Image Labeling via Exponential Integration -- On the Geometric Mechanics of Assignment Flows for Metric Data Labeling -- A Deep Image Prior Learning Algorithm for Joint Selective Segmentation and Registration -- Restoration, Reconstruction and Interpolation -- Inpainting-based Video Compression in FullHD -- Sparsity-aided Variational Mesh Restoration -- Lossless PDE-based Compression of 3D Medical Images -- Splines for Image Metamorphosis -- Residual Whiteness Principle for Automatic Parameter Selection in `2-`2 Image Super-resolution Problems -- Inverse Problems in Imaging -- Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy -- GMM-based Simultaneous Reconstruction and Segmentation in X-ray CT application -- Phase Retrieval via Polarization in Dynamical Sampling -- Invertible Neural Networks versus MCMC for Posterior Reconstruction in Grazing Incidence X-Ray Fluorescence -- Adversarially Learned Iterative Reconstruction for Imaging Inverse Problems -- Towards Off-the-grid Algorithms for Total Variation Regularized Inverse Problems -- Multi-frame Super-resolution from Noisy Data. | |
520 | _aThis book constitutes the proceedings of the 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021, which took place during May 16-20, 2021. The conference was planned to take place in Cabourg, France, but changed to an online format due to the COVID-19 pandemic. The 45 papers included in this volume were carefully reviewed and selected from a total of 64 submissions. They were organized in topical sections named as follows: scale space and partial differential equations methods; flow, motion and registration; optimization theory and methods in imaging; machine learning in imaging; segmentation and labelling; restoration, reconstruction and interpolation; and inverse problems in imaging. . | ||
650 | 0 |
_aComputer vision. _9117599 |
|
650 | 0 |
_aComputer networks . _931572 |
|
650 | 0 |
_aSocial sciences _xData processing. _983360 |
|
650 | 0 |
_aMachine learning. _91831 |
|
650 | 0 |
_aComputer science _xMathematics. _93866 |
|
650 | 0 |
_aPattern recognition systems. _93953 |
|
650 | 1 | 4 |
_aComputer Vision. _9117600 |
650 | 2 | 4 |
_aComputer Communication Networks. _9117601 |
650 | 2 | 4 |
_aComputer Application in Social and Behavioral Sciences. _931815 |
650 | 2 | 4 |
_aMachine Learning. _91831 |
650 | 2 | 4 |
_aMathematics of Computing. _931875 |
650 | 2 | 4 |
_aAutomated Pattern Recognition. _931568 |
700 | 1 |
_aElmoataz, Abderrahim. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9117602 |
|
700 | 1 |
_aFadili, Jalal. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9117603 |
|
700 | 1 |
_aQuéau, Yvain. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9117604 |
|
700 | 1 |
_aRabin, Julien. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9117605 |
|
700 | 1 |
_aSimon, Loïc. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9117606 |
|
710 | 2 |
_aSpringerLink (Online service) _9117607 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030755485 |
776 | 0 | 8 |
_iPrinted edition: _z9783030755508 |
830 | 0 |
_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12679 _9117608 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-75549-2 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
912 | _aZDB-2-LNC | ||
942 | _cELN | ||
999 |
_c90022 _d90022 |