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Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others]
| Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (784 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-78191-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Registration -- HyperMorph: Amortized Hyperparameter Learning for Image Registration -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 HyperMorph -- 3.2 Hyperparameter Tuning -- 3.3 Implementation -- 4 Experiments -- 4.1 Experiment 1: HyperMorph Efficiency and Capacity -- 4.2 Experiment 2: Robustness to Initialization -- 4.3 Experiment 3: Hyperparameter-Tuning Utility -- 5 Conclusion -- References -- Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features? -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 Methods -- 2.1 Loopy Belief Propagation for Regularised Registration of Keypoint Graphs -- 2.2 Geometric Feature Extraction with Graph Convolutional Neural Networks -- 2.3 Deep Learning Based End-to-End Geometric Registration Framework -- 2.4 Implementation Details: Keypoints, Visual Features and Integral Loss -- 3 Experiments and Results -- 4 Discussion and Conclusion -- References -- Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes -- 1 Introduction -- 2 Diffeomorphic Registration of Geometric Measures -- 2.1 Diffeomorphisms and Registration -- 2.2 Geometric Measure Representation of Shapes -- 3 Diffeomorphic Registration with Density Changes -- 3.1 An Augmented Optimal Control Problem -- 3.2 Numerical Implementation -- 3.3 Local Density Changes -- 4 Results -- 5 Conclusion -- References -- Causal Models and Interpretability -- Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum -- 1 Introduction -- 2 Methods -- 2.1 The Causal Question and Its Associated Graph -- 2.2 Identifiability in the Presence of an Unobserved Confounder -- 2.3 Estimating a Substitute Confounder -- 2.4 Identifiability in the Presence of a Substitute Confounder.
2.5 The Outcome Model -- 3 Experiments -- 4 Conclusion -- References -- Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling -- 1 Introduction -- 2 Methods -- 2.1 Notations and Formulation of Problem -- 2.2 Multiple-Shooting Method -- 2.3 Adjoint State Method -- 2.4 Multiple-Shooting Adjoint (MSA) Method -- 2.5 Dynamic Causal Modeling -- 3 Experiments -- 3.1 Validation on Toy Examples -- 3.2 Application to Whole-Brain Dynamic Causal Modeling with fMRI -- 4 Conclusion -- References -- Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Cycle-Consistent Image Simulation -- 3.2 Coupling Simulators via Conditional Convolution -- 3.3 Learning Warping Fields -- 4 Experiments -- 4.1 Synthetic Experiments -- 4.2 Visualizing the Effect of Alzheimer's Disease -- 4.3 Visualizing the Effect of Alcohol Dependence -- 5 Conclusion -- References -- Generative Modelling -- Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preliminaries -- 3.2 Regularized Adversarial Data Augmentation -- 3.3 Data Augmentation Space and Models -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Skin Lesion Diagnosis Result -- 4.3 Organ-at-Risk Segmentation Result -- 5 Conclusion -- References -- Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Microscopy Images -- 1 Introduction -- 2 Methodology -- 3 Fluorescence Unmixing -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results and Discussions -- 5 Conclusions -- References -- MR Slice Profile Estimation by Learning to Match Internal Patch Distributions -- 1 Introduction -- 2 Methods -- 2.1 Slice Profile -- 2.2 Slice Profile and Internal Patch Distributions. 2.3 Slice Profile and GAN -- 2.4 Regularization Functions and Other Details -- 3 Experiments and Results -- 3.1 Simulations from Isotropic Images -- 3.2 Incorporating Slice Profile Estimation into SMORE -- 3.3 Measuring Through-Plane Resolution After Applying SMORE -- 4 Discussion and Conclusions -- References -- Shape -- Partial Matching in the Space of Varifolds -- 1 Introduction -- 2 Partial Matching -- 2.1 The Varifold Framework for Shape Matching -- 2.2 Definition of the Partial Matching Dissimilarity -- 2.3 Normalized Partial Matching Dissimilarity -- 2.4 Use in the LDDMM Setting -- 3 Experiments -- 4 Conclusion -- References -- Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis -- 1 Introduction -- 2 Nested Grassmannians -- 2.1 The Riemannian Geometry of Grassmann Manifolds -- 2.2 Embedding of Gr(p, m) in Gr(p, n) -- 2.3 Unsupervised Dimensionality Reduction -- 2.4 Supervised Dimensionality Reduction -- 2.5 Choice of the Distance d -- 2.6 Analysis of Principal Nested Grassmanns -- 3 Experiments -- 3.1 Synthetic Data -- 3.2 Application to Planar Shape Analysis -- 4 Conclusion -- References -- Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images -- 1 Introduction -- 2 Methods -- 2.1 Tooth Centroid and Skeleton Extraction Network -- 2.2 Multi-task Learning for Tooth Segmentation -- 2.3 Implementation Details -- 3 Experimental Results -- 3.1 Dataset and Evaluation Metrics -- 3.2 Evaluation and Comparison -- 3.3 Comparison with the State-of-the-Art Methods -- 4 Conclusion -- References -- Cortical Morphometry Analysis Based on Worst Transportation Theory -- 1 Introduction -- 2 Theoretic Results -- 2.1 Optimal Transportation Map -- 2.2 Worst Transportation Map -- 2.3 Geometric Variational Method -- 3 Computational Algorithms -- 3.1 Basic Concepts from Computational Geometry. 3.2 Algorithms Based on Computational Geometry -- 4 Experiments -- 5 Conclusion -- References -- Geodesic B-score for Improved Assessment of Knee Osteoarthritis -- 1 Introduction -- 2 Background -- 2.1 Shape Space -- 2.2 Geometric Statistics -- 3 Geodesic B-score -- 3.1 Generalization -- 3.2 Sex-Specific Reference -- 3.3 Algorithmic Treatment -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Efficiency of Projection Algorithm -- 4.3 Predictive Validity -- 5 Conclusion and Future Work -- References -- Brain Connectivity -- Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference -- 1 Introduction -- 2 Methods -- 2.1 Modeling the Brain Gray Matter with a 3-Compartment Model -- 2.2 An Invertible 3-Compartment Model: dMRI Summary Statistics -- 2.3 Solving the Inverse Problem via Likelihood Free Inference -- 3 Results and Discussion -- 3.1 Simulations -- 3.2 HCP MGH Results -- 4 Conclusion -- References -- Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping -- 1 Introduction -- 2 Methodology -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- Knowledge Transfer for Few-Shot Segmentation of Novel White Matter Tracts -- 1 Introduction -- 2 Methods -- 2.1 Problem Formulation and Classic Fine-Tuning -- 2.2 Knowledge Transfer for Few-Shot Segmentation of Novel WM Tracts -- 2.3 A Better Implementation with Warmup -- 2.4 Implementation Details -- 3 Results -- 3.1 Data Description and Experimental Settings -- 3.2 Evaluation of Segmentation Accuracy -- 3.3 Impact of the Number of Annotated Training Scans -- 3.4 Evaluation of Volume Difference -- 4 Discussion -- 5 Conclusion -- References -- Discovering Spreading Pathways of Neuropathological Events in Alzheimer's Disease Using Harmonic Wavelets -- 1 Introduction -- 2 Methods -- 2.1 Manifold Harmonics. 2.2 Construction of Region-Adaptive Harmonic Wavelets -- 3 Experiments -- 3.1 Evaluate the Representation Power on Harmonic Wavelets -- 3.2 Evaluate the Statistic Power of Harmonic Wavelet Fingerprint -- 4 Conclusions -- References -- A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients -- 1 Introduction -- 2 A Multi-scale Spatial and Temporal Attention Network to Localize the Eloquent Cortex -- 2.1 Input Dynamic Connectivity Matrices -- 2.2 Multi-scale Spatial Attention on Convolutional Features -- 2.3 Temporal Attention Model and Multi-task Learning -- 3 Experimental Results -- 3.1 Dataset and Preprocessing -- 3.2 Localization Results -- 3.3 Feature Analysis -- 4 Conclusion -- References -- Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders -- 1 Introduction -- 1.1 Related Work -- 2 Proposed Method -- 2.1 Multi-resolution Graph Edge Transform -- 2.2 Efficient Graph Matrix Transform -- 2.3 Network Architecture -- 2.4 Training MENET -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Structural Brain Connectivity Analysis on ADNI -- 3.4 Functional Brain Connectivity Analysis on ADHD -- 3.5 Discussions on Convergence of Scales -- 4 Conclusion -- References -- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data -- 1 Introduction -- 2 Methods -- 2.1 Background and Preliminaries -- 2.2 Equivariant Spherical Deconvolution -- 3 Experiments -- 3.1 Noisy Synthetic Benchmark -- 3.2 The Tractometer Benchmark -- 3.3 Real-World Multi-shell Human Dataset -- 4 Discussion -- References -- Geodesic Tubes for Uncertainty Quantification in Diffusion MRI -- 1 Introduction -- 2 Theory -- 3 Experiments -- 4 Discussion -- References. Structural Connectome Atlas Construction in the Space of Riemannian Metrics. |
| Record Nr. | UNISA-996464490903316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others]
| Information processing in medical imaging : 27th International Conference, IPMI 2021, Virtual event, June 28-June 30, 2021, Proceedings / / Editor, Aasa Feragen [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (784 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-78191-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Registration -- HyperMorph: Amortized Hyperparameter Learning for Image Registration -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 HyperMorph -- 3.2 Hyperparameter Tuning -- 3.3 Implementation -- 4 Experiments -- 4.1 Experiment 1: HyperMorph Efficiency and Capacity -- 4.2 Experiment 2: Robustness to Initialization -- 4.3 Experiment 3: Hyperparameter-Tuning Utility -- 5 Conclusion -- References -- Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features? -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 Methods -- 2.1 Loopy Belief Propagation for Regularised Registration of Keypoint Graphs -- 2.2 Geometric Feature Extraction with Graph Convolutional Neural Networks -- 2.3 Deep Learning Based End-to-End Geometric Registration Framework -- 2.4 Implementation Details: Keypoints, Visual Features and Integral Loss -- 3 Experiments and Results -- 4 Discussion and Conclusion -- References -- Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes -- 1 Introduction -- 2 Diffeomorphic Registration of Geometric Measures -- 2.1 Diffeomorphisms and Registration -- 2.2 Geometric Measure Representation of Shapes -- 3 Diffeomorphic Registration with Density Changes -- 3.1 An Augmented Optimal Control Problem -- 3.2 Numerical Implementation -- 3.3 Local Density Changes -- 4 Results -- 5 Conclusion -- References -- Causal Models and Interpretability -- Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's Continuum -- 1 Introduction -- 2 Methods -- 2.1 The Causal Question and Its Associated Graph -- 2.2 Identifiability in the Presence of an Unobserved Confounder -- 2.3 Estimating a Substitute Confounder -- 2.4 Identifiability in the Presence of a Substitute Confounder.
2.5 The Outcome Model -- 3 Experiments -- 4 Conclusion -- References -- Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modeling -- 1 Introduction -- 2 Methods -- 2.1 Notations and Formulation of Problem -- 2.2 Multiple-Shooting Method -- 2.3 Adjoint State Method -- 2.4 Multiple-Shooting Adjoint (MSA) Method -- 2.5 Dynamic Causal Modeling -- 3 Experiments -- 3.1 Validation on Toy Examples -- 3.2 Application to Whole-Brain Dynamic Causal Modeling with fMRI -- 4 Conclusion -- References -- Going Beyond Saliency Maps: Training Deep Models to Interpret Deep Models -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Cycle-Consistent Image Simulation -- 3.2 Coupling Simulators via Conditional Convolution -- 3.3 Learning Warping Fields -- 4 Experiments -- 4.1 Synthetic Experiments -- 4.2 Visualizing the Effect of Alzheimer's Disease -- 4.3 Visualizing the Effect of Alcohol Dependence -- 5 Conclusion -- References -- Generative Modelling -- Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Preliminaries -- 3.2 Regularized Adversarial Data Augmentation -- 3.3 Data Augmentation Space and Models -- 4 Experiments -- 4.1 Experiments Setup -- 4.2 Skin Lesion Diagnosis Result -- 4.3 Organ-at-Risk Segmentation Result -- 5 Conclusion -- References -- Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Microscopy Images -- 1 Introduction -- 2 Methodology -- 3 Fluorescence Unmixing -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results and Discussions -- 5 Conclusions -- References -- MR Slice Profile Estimation by Learning to Match Internal Patch Distributions -- 1 Introduction -- 2 Methods -- 2.1 Slice Profile -- 2.2 Slice Profile and Internal Patch Distributions. 2.3 Slice Profile and GAN -- 2.4 Regularization Functions and Other Details -- 3 Experiments and Results -- 3.1 Simulations from Isotropic Images -- 3.2 Incorporating Slice Profile Estimation into SMORE -- 3.3 Measuring Through-Plane Resolution After Applying SMORE -- 4 Discussion and Conclusions -- References -- Shape -- Partial Matching in the Space of Varifolds -- 1 Introduction -- 2 Partial Matching -- 2.1 The Varifold Framework for Shape Matching -- 2.2 Definition of the Partial Matching Dissimilarity -- 2.3 Normalized Partial Matching Dissimilarity -- 2.4 Use in the LDDMM Setting -- 3 Experiments -- 4 Conclusion -- References -- Nested Grassmanns for Dimensionality Reduction with Applications to Shape Analysis -- 1 Introduction -- 2 Nested Grassmannians -- 2.1 The Riemannian Geometry of Grassmann Manifolds -- 2.2 Embedding of Gr(p, m) in Gr(p, n) -- 2.3 Unsupervised Dimensionality Reduction -- 2.4 Supervised Dimensionality Reduction -- 2.5 Choice of the Distance d -- 2.6 Analysis of Principal Nested Grassmanns -- 3 Experiments -- 3.1 Synthetic Data -- 3.2 Application to Planar Shape Analysis -- 4 Conclusion -- References -- Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Images -- 1 Introduction -- 2 Methods -- 2.1 Tooth Centroid and Skeleton Extraction Network -- 2.2 Multi-task Learning for Tooth Segmentation -- 2.3 Implementation Details -- 3 Experimental Results -- 3.1 Dataset and Evaluation Metrics -- 3.2 Evaluation and Comparison -- 3.3 Comparison with the State-of-the-Art Methods -- 4 Conclusion -- References -- Cortical Morphometry Analysis Based on Worst Transportation Theory -- 1 Introduction -- 2 Theoretic Results -- 2.1 Optimal Transportation Map -- 2.2 Worst Transportation Map -- 2.3 Geometric Variational Method -- 3 Computational Algorithms -- 3.1 Basic Concepts from Computational Geometry. 3.2 Algorithms Based on Computational Geometry -- 4 Experiments -- 5 Conclusion -- References -- Geodesic B-score for Improved Assessment of Knee Osteoarthritis -- 1 Introduction -- 2 Background -- 2.1 Shape Space -- 2.2 Geometric Statistics -- 3 Geodesic B-score -- 3.1 Generalization -- 3.2 Sex-Specific Reference -- 3.3 Algorithmic Treatment -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Efficiency of Projection Algorithm -- 4.3 Predictive Validity -- 5 Conclusion and Future Work -- References -- Brain Connectivity -- Cytoarchitecture Measurements in Brain Gray Matter Using Likelihood-Free Inference -- 1 Introduction -- 2 Methods -- 2.1 Modeling the Brain Gray Matter with a 3-Compartment Model -- 2.2 An Invertible 3-Compartment Model: dMRI Summary Statistics -- 2.3 Solving the Inverse Problem via Likelihood Free Inference -- 3 Results and Discussion -- 3.1 Simulations -- 3.2 HCP MGH Results -- 4 Conclusion -- References -- Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain Mapping -- 1 Introduction -- 2 Methodology -- 3 Experimental Results and Discussion -- 4 Conclusion -- References -- Knowledge Transfer for Few-Shot Segmentation of Novel White Matter Tracts -- 1 Introduction -- 2 Methods -- 2.1 Problem Formulation and Classic Fine-Tuning -- 2.2 Knowledge Transfer for Few-Shot Segmentation of Novel WM Tracts -- 2.3 A Better Implementation with Warmup -- 2.4 Implementation Details -- 3 Results -- 3.1 Data Description and Experimental Settings -- 3.2 Evaluation of Segmentation Accuracy -- 3.3 Impact of the Number of Annotated Training Scans -- 3.4 Evaluation of Volume Difference -- 4 Discussion -- 5 Conclusion -- References -- Discovering Spreading Pathways of Neuropathological Events in Alzheimer's Disease Using Harmonic Wavelets -- 1 Introduction -- 2 Methods -- 2.1 Manifold Harmonics. 2.2 Construction of Region-Adaptive Harmonic Wavelets -- 3 Experiments -- 3.1 Evaluate the Representation Power on Harmonic Wavelets -- 3.2 Evaluate the Statistic Power of Harmonic Wavelet Fingerprint -- 4 Conclusions -- References -- A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients -- 1 Introduction -- 2 A Multi-scale Spatial and Temporal Attention Network to Localize the Eloquent Cortex -- 2.1 Input Dynamic Connectivity Matrices -- 2.2 Multi-scale Spatial Attention on Convolutional Features -- 2.3 Temporal Attention Model and Multi-task Learning -- 3 Experimental Results -- 3.1 Dataset and Preprocessing -- 3.2 Localization Results -- 3.3 Feature Analysis -- 4 Conclusion -- References -- Learning Multi-resolution Graph Edge Embedding for Discovering Brain Network Dysfunction in Neurological Disorders -- 1 Introduction -- 1.1 Related Work -- 2 Proposed Method -- 2.1 Multi-resolution Graph Edge Transform -- 2.2 Efficient Graph Matrix Transform -- 2.3 Network Architecture -- 2.4 Training MENET -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Structural Brain Connectivity Analysis on ADNI -- 3.4 Functional Brain Connectivity Analysis on ADHD -- 3.5 Discussions on Convergence of Scales -- 4 Conclusion -- References -- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data -- 1 Introduction -- 2 Methods -- 2.1 Background and Preliminaries -- 2.2 Equivariant Spherical Deconvolution -- 3 Experiments -- 3.1 Noisy Synthetic Benchmark -- 3.2 The Tractometer Benchmark -- 3.3 Real-World Multi-shell Human Dataset -- 4 Discussion -- References -- Geodesic Tubes for Uncertainty Quantification in Diffusion MRI -- 1 Introduction -- 2 Theory -- 3 Experiments -- 4 Discussion -- References. Structural Connectome Atlas Construction in the Space of Riemannian Metrics. |
| Record Nr. | UNINA-9910485594103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Similarity-Based Pattern Recognition [[electronic resource] ] : Third International Workshop, SIMBAD 2015, Copenhagen, Denmark, October 12-14, 2015. Proceedings / / edited by Aasa Feragen, Marcello Pelillo, Marco Loog
| Similarity-Based Pattern Recognition [[electronic resource] ] : Third International Workshop, SIMBAD 2015, Copenhagen, Denmark, October 12-14, 2015. Proceedings / / edited by Aasa Feragen, Marcello Pelillo, Marco Loog |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (VIII, 229 p. 78 illus.) |
| Disciplina | 006.4 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Database management Algorithms Application software Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Database Management Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) |
| ISBN | 3-319-24261-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Novel Data Representation based on a Second-Order Dissimilarity Measure -- Characterizing Multiple Instance Datasets -- Supervised learning of diffiusion distance to improve histogram matching -- Similarity Analysis from Limiting Quantum Walks -- Introducing Negative Evidence in Ensemble Clustering -- Dissimilarity representations for low-resolution face recognition -- Deep metric learning using Triplet network -- Cluster Merging Based on Dominant Sets -- An Adaptive Radial Basis Function Kernel for Support Vector Data Description -- Robust initialization for learning Latent Dirichlet Allocation -- Unsupervised Motion Segmentation Using Metric Embedding of Features -- Transitive Assignment Kernels for Structural Classification -- Large scale Indefinite Kernel Fisher Discriminant -- Similarity-based User Identification across Social Networks -- Dominant-Set Clustering Using Multiple Affinity Matrices -- Distance-Based Network Recovery under Feature Correlation -- Discovery of salient low-dimensional dynamical structure using Hopfield Networks -- On Geodesic Exponential Kernels -- A Matrix Factorization Approach to Graph Compression -- A Geometrical Approach to Find Corresponding Patches in 3D Medical Surfaces -- Similarities, SDEs, and Most Probable Paths -- Can the optimum similarity matrix be selected before clustering for graph-based approaches? -- Approximate spectral clustering with utilized similarity information fusing geodesic based hybrid distance measures. |
| Record Nr. | UNISA-996466318103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Copenhagen, Denmark, October 12-14, 2015. Proceedings / / edited by Aasa Feragen, Marcello Pelillo, Marco Loog
| Similarity-Based Pattern Recognition : Third International Workshop, SIMBAD 2015, Copenhagen, Denmark, October 12-14, 2015. Proceedings / / edited by Aasa Feragen, Marcello Pelillo, Marco Loog |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (VIII, 229 p. 78 illus.) |
| Disciplina | 006.4 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Pattern recognition
Optical data processing Artificial intelligence Database management Algorithms Application software Pattern Recognition Image Processing and Computer Vision Artificial Intelligence Database Management Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) |
| ISBN | 3-319-24261-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Novel Data Representation based on a Second-Order Dissimilarity Measure -- Characterizing Multiple Instance Datasets -- Supervised learning of diffiusion distance to improve histogram matching -- Similarity Analysis from Limiting Quantum Walks -- Introducing Negative Evidence in Ensemble Clustering -- Dissimilarity representations for low-resolution face recognition -- Deep metric learning using Triplet network -- Cluster Merging Based on Dominant Sets -- An Adaptive Radial Basis Function Kernel for Support Vector Data Description -- Robust initialization for learning Latent Dirichlet Allocation -- Unsupervised Motion Segmentation Using Metric Embedding of Features -- Transitive Assignment Kernels for Structural Classification -- Large scale Indefinite Kernel Fisher Discriminant -- Similarity-based User Identification across Social Networks -- Dominant-Set Clustering Using Multiple Affinity Matrices -- Distance-Based Network Recovery under Feature Correlation -- Discovery of salient low-dimensional dynamical structure using Hopfield Networks -- On Geodesic Exponential Kernels -- A Matrix Factorization Approach to Graph Compression -- A Geometrical Approach to Find Corresponding Patches in 3D Medical Surfaces -- Similarities, SDEs, and Most Probable Paths -- Can the optimum similarity matrix be selected before clustering for graph-based approaches? -- Approximate spectral clustering with utilized similarity information fusing geodesic based hybrid distance measures. |
| Record Nr. | UNINA-9910484213003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||