Cargando…
A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines
The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise...
Autores principales: | Khan, Arif ul Maula, Mikut, Ralf, Reischl, Markus |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5072585/ https://www.ncbi.nlm.nih.gov/pubmed/27764213 http://dx.doi.org/10.1371/journal.pone.0165180 |
Ejemplares similares
-
A Benchmark Data Set to Evaluate the Illumination Robustness of Image Processing Algorithms for Object Segmentation and Classification
por: Khan, Arif ul Maula, et al.
Publicado: (2015) -
AutoCellSeg: robust automatic colony forming unit (CFU)/cell analysis using adaptive image segmentation and easy-to-use post-editing techniques
por: Khan, Arif ul Maula, et al.
Publicado: (2018) -
Enhancing deep-learning training for phase identification in powder X-ray diffractograms
por: Schuetzke, Jan, et al.
Publicado: (2021) -
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images
por: Scherr, Tim, et al.
Publicado: (2020) -
Motion prediction enables simulated MR-imaging of freely moving model organisms
por: Reischl, Markus, et al.
Publicado: (2019)