- Sprache
-
Englisch
- Identifier
-
1313985570
- Thema
-
Neuronales Netz; Maschinelles Lernen; Deep learning; Merkmalsextraktion; Mustererkennung; Maschinelles Sehen
- Beteiligte Personen und Organisationen
-
Uhlemeyer, Svenja
- URN
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
09.01.2024, 11:56 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.
Objekttyp
- Monografie
Beteiligte
- Uhlemeyer, Svenja
Ähnliche Objekte (12)
Unsupervised object candidate discovery for activity recognition
Unsupervised relational feature learning for vision
Unsupervised learning in cross-corpus acoustic emotion recognition
Autoencoder-based unsupervised domain adaptation for speech emotion recognition
NEER: An unsupervised method for named entity evolution recognition
Vision-based open set recognition for industrial inspection systems
Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition
Object recognition in active vision
Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques
World Vision
World Vision
Computer vision : detection, recognition and reconstruction
Unsupervised object candidate discovery for activity recognition
Unsupervised relational feature learning for vision
Unsupervised learning in cross-corpus acoustic emotion recognition
Autoencoder-based unsupervised domain adaptation for speech emotion recognition
NEER: An unsupervised method for named entity evolution recognition
Vision-based open set recognition for industrial inspection systems
Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition
Object recognition in active vision
Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques
World Vision
World Vision
Computer vision : detection, recognition and reconstruction
Unsupervised object candidate discovery for activity recognition
Unsupervised relational feature learning for vision
Unsupervised learning in cross-corpus acoustic emotion recognition
Autoencoder-based unsupervised domain adaptation for speech emotion recognition
NEER: An unsupervised method for named entity evolution recognition
Vision-based open set recognition for industrial inspection systems
Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition
Object recognition in active vision
Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques
World Vision
World Vision