- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 11 Seiten
- Sprache
-
Englisch
- Erschienen in
-
In: The visual computer(38), H. 12, S.4071-4081 - ISSN 1432-2315
In: Springer, Berlin
- Ereignis
-
Veröffentlichung
- (wo)
-
Ilmenau
- (wer)
-
TU Ilmenau
- (wann)
-
2022
- Urheber
- DOI
-
10.1007/s00371-022-02531-0
- URN
-
urn:nbn:de:101:1-2024021202063650647603
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:54 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
- Kunert, Christian
- Schwandt, Tobias
- Nadar, Christon R.
- Broll, Wolfgang
- TU Ilmenau
Entstanden
- 2022
Ähnliche Objekte (12)
Representation of depth in neural population responses
Representation of depth in neural population responses
Calibrating Depth Sensors with a Genetic Algorithm
Replication of chaos in neural networks, economics and physics
Event-based Depth Reconstruction Using Stereo Dynamic Vision Sensors
Predicting Student Dropout: A Replication Study Based on Neural Networks
Learning and Replication of Periodic Signals in Neural-Like Networks
Time-of-flight and depth imaging : sensors, algorithms, and applications
Depth perception in frogs and toads : a study in neural computing
Field evaluation of a novel holographic single-image depth reconstruction sensor
Processing and tracking human motions using optical, inertial, and depth sensors
Adaption
Representation of depth in neural population responses
Representation of depth in neural population responses
Calibrating Depth Sensors with a Genetic Algorithm
Replication of chaos in neural networks, economics and physics
Event-based Depth Reconstruction Using Stereo Dynamic Vision Sensors
Predicting Student Dropout: A Replication Study Based on Neural Networks
Learning and Replication of Periodic Signals in Neural-Like Networks
Time-of-flight and depth imaging : sensors, algorithms, and applications
Depth perception in frogs and toads : a study in neural computing
Field evaluation of a novel holographic single-image depth reconstruction sensor
Processing and tracking human motions using optical, inertial, and depth sensors
Adaption
Representation of depth in neural population responses
Representation of depth in neural population responses
Calibrating Depth Sensors with a Genetic Algorithm
Replication of chaos in neural networks, economics and physics
Event-based Depth Reconstruction Using Stereo Dynamic Vision Sensors
Predicting Student Dropout: A Replication Study Based on Neural Networks
Learning and Replication of Periodic Signals in Neural-Like Networks
Time-of-flight and depth imaging : sensors, algorithms, and applications
Depth perception in frogs and toads : a study in neural computing
Field evaluation of a novel holographic single-image depth reconstruction sensor
Processing and tracking human motions using optical, inertial, and depth sensors