Cargando…
Pilot Behavior Recognition Based on Multi-Modality Fusion Technology Using Physiological Characteristics
With the development of the autopilot system, the main task of a pilot has changed from controlling the aircraft to supervising the autopilot system and making critical decisions. Therefore, the human–machine interaction system needs to be improved accordingly. A key step to improving the human–mach...
Autores principales: | Li, Yuhan, Li, Ke, Wang, Shaofan, Chen, Xiaodan, Wen, Dongsheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221330/ https://www.ncbi.nlm.nih.gov/pubmed/35735552 http://dx.doi.org/10.3390/bios12060404 |
Ejemplares similares
-
Recognition of multi-modal fusion images with irregular interference
por: Wang, Yawei, et al.
Publicado: (2022) -
Emotion recognition based on multi-modal physiological signals and transfer learning
por: Fu, Zhongzheng, et al.
Publicado: (2022) -
Interpretable Passive Multi-Modal Sensor Fusion for Human Identification and Activity Recognition
por: Yuan, Liangqi, et al.
Publicado: (2022) -
Multi-Modal Fusion Emotion Recognition Method of Speech Expression Based on Deep Learning
por: Liu, Dong, et al.
Publicado: (2021) -
Semi-Supervised Cross-Subject Emotion Recognition Based on Stacked Denoising Autoencoder Architecture Using a Fusion of Multi-Modal Physiological Signals
por: Luo, Junhai, et al.
Publicado: (2022)