Towards a Universally Applicable Neural State Estimation through Transfer Learning.
Stephan BalduinEric M. S. P. VeithAlexander BerezinSebastian LehnhoffThomas OberließenChris KittlJohannes HiryChristian RehtanzGiancarlo Torres-VillarrealSasiphong LeksawatAndreas KubisMarc-Aurel FrankenbachPublished in: ISGT-Europe (2021)
Keyphrases
- transfer learning
- state estimation
- knowledge transfer
- kalman filter
- dynamic systems
- labeled data
- kalman filtering
- cross domain
- particle filter
- reinforcement learning
- machine learning
- particle filtering
- semi supervised learning
- active learning
- text classification
- neural network
- visual tracking
- multi task
- transfer knowledge
- text categorization
- text mining
- collaborative filtering
- unlabeled data
- domain adaptation
- supervised learning
- multi sensor
- target domain
- learning algorithm