- Weitere Titel
-
Deep Learning Trifft Auf Visuelle Lokalisierung
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
München, Technische Universität München, Dissertation, 2023
- Schlagwort
-
Maschinelles Sehen
Merkmalsextraktion
Objekterkennung
Kamera
Maschinelles Lernen
Szenenanalyse
- Ereignis
-
Veröffentlichung
- (wo)
-
München
- (wer)
-
Universitätsbibliothek der TU München
- (wann)
-
2023
- Urheber
-
Zhou, Qunjie
- Beteiligte Personen und Organisationen
- URN
-
urn:nbn:de:bvb:91-diss-20230706-1693333-1-0
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:49 MEZ
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
- Zhou, Qunjie
- Leal-Taixé, Laura
- Pollefeys, Marc
- Matas, Jiri
- Universitätsbibliothek der TU München
Entstanden
- 2023
Ähnliche Objekte (12)
Robust and Efficient Deep Visual Learning
Linguistic interpretation of visual contents via Deep Learning
Simulation meets real-world : deep reinforcement learning on inverted pendulum system
Deep Neural Nets meets ODE's
Visual Localization with Lines
Visual localization with lines
Deep learning on point clouds with applications in vehicle self-localization
Deep learning on point clouds with applications in vehicle self-localization
Speaker identification and localization using shuffled MFCC features and deep learning
Deep Learning Methods for Vehicle Localization and Control under Challenging Conditions
Source Localization in Reverberant Rooms using Deep Learning and Microphone Arrays
Learning deep visual features for Minimum Cost Multicut Problem
Robust and Efficient Deep Visual Learning
Linguistic interpretation of visual contents via Deep Learning
Simulation meets real-world : deep reinforcement learning on inverted pendulum system
Deep Neural Nets meets ODE's
Visual Localization with Lines
Visual localization with lines
Deep learning on point clouds with applications in vehicle self-localization
Deep learning on point clouds with applications in vehicle self-localization
Speaker identification and localization using shuffled MFCC features and deep learning
Deep Learning Methods for Vehicle Localization and Control under Challenging Conditions
Source Localization in Reverberant Rooms using Deep Learning and Microphone Arrays
Learning deep visual features for Minimum Cost Multicut Problem
Robust and Efficient Deep Visual Learning
Linguistic interpretation of visual contents via Deep Learning
Simulation meets real-world : deep reinforcement learning on inverted pendulum system
Deep Neural Nets meets ODE's
Visual Localization with Lines
Visual localization with lines
Deep learning on point clouds with applications in vehicle self-localization
Deep learning on point clouds with applications in vehicle self-localization
Speaker identification and localization using shuffled MFCC features and deep learning
Deep Learning Methods for Vehicle Localization and Control under Challenging Conditions
Source Localization in Reverberant Rooms using Deep Learning and Microphone Arrays