LAUSR

Robust modeling of epistemic mental states

Sign Up to like & get
recommendations!
0 Published in 2020 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-020-09145-5

Abstract: This work identifies and advances some research challenges in the analysis of facial features and their temporal dynamics with epistemic mental states in dyadic conversations. Epistemic states are: Agreement, Concentration, Thoughtful, Certain, and Interest. In… read more here.

Keywords: robust modeling; facial features; epistemic mental; modeling epistemic ... See more keywords

Robust Modeling of GNSS Tropospheric Delay Dynamics

Sign Up to like & get
recommendations!
0 Published in 2021 at "IEEE Transactions on Aerospace and Electronic Systems"

DOI: 10.1109/taes.2021.3068441

Abstract: In this article, we develop new stochastic tropospheric error models for positioning, fault detection, and integrity monitoring over time. We first perform time-domain and frequency-domain analyses of residual tropospheric delays observed over 12 months at… read more here.

Keywords: robust modeling; time; tropospheric delay; delay dynamics ... See more keywords

Physical Informed Sparse Learning for Robust Modeling of Distributed Parameter System and Its Industrial Applications

Sign Up to like & get
recommendations!
0 Published in 2024 at "IEEE Transactions on Automation Science and Engineering"

DOI: 10.1109/tase.2023.3298806

Abstract: With the development of information technologies, a large number of sensors have been deployed to obtain industrial data. As a result, data-driven approaches have become a crucial means for modeling of distributed parameter systems (DPS).… read more here.

Keywords: modeling distributed; method; physical informed; robust modeling ... See more keywords

Robust Modeling for Industrial Process Based on Frequency Reconstructed Fuzzy Neural Network

Sign Up to like & get
recommendations!
0 Published in 2024 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2023.3291488

Abstract: The model bias caused by input outliers is a dramatic obstacle to the application of models in industrial processes. To cope with this problem, this article proposes a robust modeling method based on frequency reconstructed… read more here.

Keywords: fuzzy neural; robust modeling; reconstructed fuzzy; based frequency ... See more keywords