From hard to soft: towards more human-like emotion recognition by modelling the perception uncertainty
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: Proceedings of the 2017 ACM on Multimedia Conference - MM '17, Mountain View, California, USA, October 23 - 27, 2017, S. 890-897
- Ereignis
-
Veröffentlichung
- (wo)
-
Augsburg, New York, NY
- (wer)
-
Universität Augsburg, ACM Press
- (wann)
-
2017
- Urheber
- Beteiligte Personen und Organisationen
- DOI
-
10.1145/3123266.3123383
- URN
-
urn:nbn:de:bvb:384-opus4-450696
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:53 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
- Han, Jing
- Zhang, Zixing
- Schmitt, Maximilian
- Pantic, Maja
- Schuller, Björn
- Liu, Qiong
- Lienhart, Rainer
- Wang, Haohong
- Universität Augsburg, ACM Press
Entstanden
- 2017
Ähnliche Objekte (12)
The fertilized forests decision forest library
Deriving a discriminative color model for a given object class from weakly labeled training data
Audio brush: a tool for computer-assisted smart audio editing
Bundle min-hashing for logo recognition
Deep networks for image retrieval on large-scale databases
Visual question answering with a hybrid convolution recurrent model
On the benefit of synthetic data for company logo detection
Towards automatic object annotations from global image labels
Scalable logo recognition in real-world images
Synthetically trained multi-view object class and viewpoint detection for advanced image retrieval
Improving small object proposals for company logo detection
Augment to prevent: short-text data augmentation in deep learning for hate-speech classification
The fertilized forests decision forest library
Deriving a discriminative color model for a given object class from weakly labeled training data
Audio brush: a tool for computer-assisted smart audio editing
Bundle min-hashing for logo recognition
Deep networks for image retrieval on large-scale databases
Visual question answering with a hybrid convolution recurrent model
On the benefit of synthetic data for company logo detection
Towards automatic object annotations from global image labels
Scalable logo recognition in real-world images
Synthetically trained multi-view object class and viewpoint detection for advanced image retrieval
Improving small object proposals for company logo detection
Augment to prevent: short-text data augmentation in deep learning for hate-speech classification
The fertilized forests decision forest library
Deriving a discriminative color model for a given object class from weakly labeled training data
Audio brush: a tool for computer-assisted smart audio editing
Bundle min-hashing for logo recognition
Deep networks for image retrieval on large-scale databases
Visual question answering with a hybrid convolution recurrent model
On the benefit of synthetic data for company logo detection
Towards automatic object annotations from global image labels
Scalable logo recognition in real-world images
Synthetically trained multi-view object class and viewpoint detection for advanced image retrieval
Improving small object proposals for company logo detection