Compressed Sensing via Measurement-Conditional Generative Models
Pre-trained generators have been frequently adopted in compressed sensing (CS) owing to their ability to effectively estimate signals with the prior of NNs. To further refine the NN-based prior, we propose a framework that allows the generator to utilize additional information from given measurement...
Guardado en:
Autores principales: | Kyung-Su Kim, Jung Hyun Lee, Eunho Yang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/bba1dc7b48244d7eade5d2db3dcb8225 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
REDUCCIÓN DE LOS TIEMPOS DE ADQUISICIÓN DE IMÁGENES POR RESONANCIA MAGNÉTICA UTILIZANDO TÉCNICAS DE COMPRESSED SENSING
por: Sing-Long C,Carlos, et al.
Publicado: (2009) -
Soft computing based compressive sensing techniques in signal processing: A comprehensive review
por: Mishra Ishani, et al.
Publicado: (2020) -
A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures
por: Tiehua Zhao, et al.
Publicado: (2021) -
ECG Monitoring Based on Dynamic Compressed Sensing of Multi-Lead Signals
por: Pasquale Daponte, et al.
Publicado: (2021) -
Textured Mesh Generation Using Multi-View and Multi-Source Supervision and Generative Adversarial Networks
por: Mingyun Wen, et al.
Publicado: (2021)