Cargando…
Context-Unsupervised Adversarial Network for Video Sensors †
Foreground object segmentation is a crucial first step for surveillance systems based on networks of video sensors. This problem in the context of dynamic scenes has been widely explored in the last two decades, but it still has open research questions due to challenges such as strong shadows, backg...
Autores principales: | Canet Tarrés, Gemma, Pardàs, Montse |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9102692/ https://www.ncbi.nlm.nih.gov/pubmed/35590863 http://dx.doi.org/10.3390/s22093171 |
Ejemplares similares
-
Unsupervised anomaly detection with generative adversarial networks in mammography
por: Park, Seungju, et al.
Publicado: (2023) -
Unsupervised Anomaly Detection of Healthcare Providers Using Generative Adversarial Networks
por: Naidoo, Krishnan, et al.
Publicado: (2020) -
Unsupervised Low-Light Image Enhancement Based on Generative Adversarial Network
por: Yu, Wenshuo, et al.
Publicado: (2023) -
Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network
por: Zhao, Liquan, et al.
Publicado: (2023) -
Publisher Correction: Unsupervised anomaly detection with generative adversarial networks in mammography
por: Park, Seungju, et al.
Publicado: (2023)