A Pattern Recognition Tool for Medium-Resolution Cryo-EM Density Maps and Low-Resolution Cryo-ET Density Maps

2018 ◽  
pp. 233-238 ◽  
Author(s):  
Devin Haslam ◽  
Salim Sazzed ◽  
Willy Wriggers ◽  
Julio Kovacs ◽  
Junha Song ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Low Resolution ◽  
Density Maps ◽  
Medium Resolution

scholarly journals Mapping the Unseen: Exploiting Super-Resolution for Semantic Segmentation in Low-Resolution Images

2020 ◽  
Author(s):  
Matheus B. Pereira ◽  
Jefersson Alex Dos Santos
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition ◽  
Super Resolution ◽  
Remote Sensing Data ◽  
Semantic Segmentation ◽  
The Other ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Remote Sensing Images ◽  
Low Resolution

High-resolution aerial images are usually not accessible or affordable. On the other hand, low-resolution remote sensing data is easily found in public open repositories. The problem is that the low-resolution representation can compromise pattern recognition algorithms, especially semantic segmentation. In this M.Sc. dissertation1 , we design two frameworks in order to evaluate the effectiveness of super-resolution in the semantic segmentation of low-resolution remote sensing images. We carried out an extensive set of experiments on different remote sensing datasets. The results show that super-resolution is effective to improve semantic segmentation performance on low-resolution aerial imagery, outperforming unsupervised interpolation and achieving semantic segmentation results comparable to highresolution data.

scholarly journals LiDAR resolution for catchment-inclusive hydrodynamic models

2018 ◽  
Vol 40 ◽  
pp. 06031
Author(s):  
Graeme Smart
Keyword(s):  
Flood Mapping ◽  
Hydrodynamic Modelling ◽  
Low Resolution ◽  
Hydrodynamic Models ◽  
Model Accuracy ◽  
Control Structures ◽  
High Point ◽  
Medium Resolution ◽  
Point Density

Hydrodynamic models are usually based on LiDAR but there is little information on the LiDAR resolution required for appropriate model accuracy. In this study, algorithms to prepare DEM and roughness grids suitable for hydrodynamic modelling of both catchment and floodplain are applied to low, medium and high point-density LiDAR. The medium resolution LiDAR (9 points/m2) provided elevation and roughness grids sufficiently accurate for hydrodynamic flood mapping of urban and rural floodplains. Low-resolution LiDAR (3 points/m2) is considered adequate for hill catchments. Attention is required where narrow-crested control structures exist. Mapping and upscaling are discussed.

scholarly journals Cylindrical Similarity Measurement for Helices in Medium-Resolution Cryo-Electron Microscopy Density Maps

2020 ◽  
Vol 60 (5) ◽  
pp. 2644-2650 ◽  
Author(s):  
Salim Sazzed ◽  
Peter Scheible ◽  
Maytha Alshammari ◽  
Willy Wriggers ◽  
Jing He
Keyword(s):  
Electron Microscopy ◽  
Similarity Measurement ◽  
Cryo Electron Microscopy ◽  
Density Maps ◽  
Medium Resolution
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