- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Heidelberg, Universität Heidelberg, Dissertation, 2020
- Klassifikation
-
Informatik
- Schlagwort
-
Labels
Bildsegmentierung
Gradientenfluss
Bilderkennung
- Ereignis
-
Veröffentlichung
- (wo)
-
Heidelberg
- (wer)
-
Universitätsbibliothek Heidelberg
- (wann)
-
2020
- Urheber
- Beteiligte Personen und Organisationen
- DOI
-
10.11588/heidok.00028522
- URN
-
urn:nbn:de:bsz:16-heidok-285225
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:53 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Savarino, Fabrizio
- Schnörr, Christoph
- Universitätsbibliothek Heidelberg
Entstanden
- 2020
Ähnliche Objekte (12)
Inference and Model Parameter Learning for Image Labeling by Geometric Assignment
Learning Linearized Assignment Flows for Image Labeling
Assignment flows for data labeling on graphs: convergence and stability
On the geometric mechanics of assignment flows for metric data labeling
Continuous Multiclass Labeling Approaches and Algorithms
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
Unsupervised Data Labeling on Graphs by Self‐Assignment Flows
On the Correspondence between Replicator Dynamics and Assignment Flows
Riemannian Flows for Supervised and Unsupervised Geometric Image Labeling
Nonlocal Graph-PDEs and Riemannian Gradient Flows for Image Labeling
New Convex Relaxations and Global Optimality in Variational Imaging
Variational Approaches for Motion and Structure from Monocular Video
Inference and Model Parameter Learning for Image Labeling by Geometric Assignment
Learning Linearized Assignment Flows for Image Labeling
Assignment flows for data labeling on graphs: convergence and stability
On the geometric mechanics of assignment flows for metric data labeling
Continuous Multiclass Labeling Approaches and Algorithms
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
Unsupervised Data Labeling on Graphs by Self‐Assignment Flows
On the Correspondence between Replicator Dynamics and Assignment Flows
Riemannian Flows for Supervised and Unsupervised Geometric Image Labeling
Nonlocal Graph-PDEs and Riemannian Gradient Flows for Image Labeling
New Convex Relaxations and Global Optimality in Variational Imaging
Variational Approaches for Motion and Structure from Monocular Video
Inference and Model Parameter Learning for Image Labeling by Geometric Assignment
Learning Linearized Assignment Flows for Image Labeling
Assignment flows for data labeling on graphs: convergence and stability
On the geometric mechanics of assignment flows for metric data labeling
Continuous Multiclass Labeling Approaches and Algorithms
Learning Adaptive Regularization for Image Labeling Using Geometric Assignment
Unsupervised Data Labeling on Graphs by Self‐Assignment Flows
On the Correspondence between Replicator Dynamics and Assignment Flows
Riemannian Flows for Supervised and Unsupervised Geometric Image Labeling
Nonlocal Graph-PDEs and Riemannian Gradient Flows for Image Labeling
New Convex Relaxations and Global Optimality in Variational Imaging