Rapid Labels: Point-Feature Labeling on GPU

2021 ◽  
pp. 1-1
Author(s):  
Vaclav Pavlovec ◽  
Ladislav Cmolik
Keyword(s):  
Point Feature

3D mixed CNNs with edge-point feature learning

2021 ◽  
pp. 106985
Author(s):  
Zijin Du ◽  
Hailiang Ye ◽  
Feilong Cao
Keyword(s):  
Feature Learning ◽  
Edge Point ◽  
Point Feature

scholarly journals A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fatemeh Hashemi Amin ◽  
Mahtab Ghaemi ◽  
Sayyed Mostafa Mostafavi ◽  
Ladan Goshayeshi ◽  
Khadijeh Rezaei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Cancer Patients ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Dietary Habits ◽  
Age Groups ◽  
Geographical Location ◽  
Geographical Information ◽  
Point Feature

Abstract Objectives Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran. Data description We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

A shadow-removal based saliency map for point feature detection of underwater objects

2015 ◽  
Author(s):  
Liqin Fu ◽  
Yiru Wang ◽  
Zhebin Zhang ◽  
Rui Nian ◽  
Tianhong Yan ◽  
...  
Keyword(s):  
Feature Detection ◽  
Saliency Map ◽  
Shadow Removal ◽  
Point Feature

Point Feature Label Placement for Multi-Page Maps on Small-Screen Devices

2021 ◽  
Author(s):  
Sven Gedicke ◽  
Adalat Jabrayilov ◽  
Benjamin Niedermann ◽  
Petra Mutzel ◽  
Jan-Henrik Haunert
Keyword(s):  
Label Placement ◽  
Small Screen Devices ◽  
Small Screen ◽  
Point Feature

scholarly journals Dimensionality reduction for point feature SLAM problems with spherical covariance matrices

Automatica ◽  
2015 ◽  
Vol 51 ◽  
pp. 149-157 ◽  
Author(s):  
Heng Wang ◽  
Shoudong Huang ◽  
Kasra Khosoussi ◽  
Udo Frese ◽  
Gamini Dissanayake ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Covariance Matrices ◽  
Spherical Covariance ◽  
Point Feature
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