Cargando…
A Multiscale CNN-CRF Framework for Environmental Microorganism Image Segmentation
To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. There are two parts in this framework: The first is a novel pixel-level segmentation approach, using a newly introduced Con...
Autores principales: | Zhang, Jinghua, Li, Chen, Kulwa, Frank, Zhao, Xin, Sun, Changhao, Li, Zihan, Jiang, Tao, Li, Hong, Qi, Shouliang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366198/ https://www.ncbi.nlm.nih.gov/pubmed/32724802 http://dx.doi.org/10.1155/2020/4621403 |
Ejemplares similares
-
EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks
por: Li, Zihan, et al.
Publicado: (2021) -
Low-Grade Glioma Segmentation Based on CNN with Fully Connected CRF
por: Li, Zeju, et al.
Publicado: (2017) -
Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset
por: Xu, Mingjie, et al.
Publicado: (2019) -
A novel hybrid transformer-CNN architecture for environmental microorganism classification
por: Shao, Ran, et al.
Publicado: (2022) -
EMDS-7: Environmental microorganism image dataset seventh version for multiple object detection evaluation
por: Yang, Hechen, et al.
Publicado: (2023)