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A primary challenge facing the companies commercialising fusion technology is building a supply chain, according to the Fusion Industry Association (FIA). Fusion developers are set to spend potentiall...
IDENTIFICATION OF LOW ACCURACY REGIONS IN LAND COVER MAPS USING UNCERTAINTY MEASURES AND CLASSIFICATION CONFIDENCE
Multispectral images Classification Uncertainty Confidence Accuracy Spatial variation
2018/11/9
The aim of this article is to assess if the data provided by soft classifiers and uncertainty measures can be used to identify regions with different levels of accuracy in a classified image. To this ...
IMPROVING SEMI-GLOBAL MATCHING: COST AGGREGATION AND CONFIDENCE MEASURE
Dense Matching Digital Elevation Model Stereo Benchmark Accuracy
2016/7/4
Digital elevation models are one of the basic products that can be generated from remotely sensed imagery. The Semi Global Matching (SGM) algorithm is a robust and practical algorithm for dense image ...
In 2002, Peterson, et. al. proposed using redundant signal measurements to provide the necessary confidence that the cycles are identified correctly. The proposal used a weighted sum squared error (WS...
Proving the Integrity of the Weighted Sum Squared Error (WSSE) Loran Cycle Confidence Algorithm
Proving Integrity Squared Error (WSSE) Loran Cycle Confidence Algorithm
2015/6/25
For Loran to provide redundancy to GPS for aviation,Loran must meet aviation integrity requirements. The integrity under nominal conditions derives from being able to bound the horizontal position err...
A non-conservative kinetic exchange model of opinion dynamics with randomness and bounded confidence
non-conservative kinetic exchange model opinion dynamics randomness and bounded confidence Statistical Mechanics
2012/5/17
The concept of a bounded confidence level is incorporated in a nonconservative kinetic exchange model of opinion dynamics model where opinions have continuous values $\in [-1,1]$. The characteristics ...
Introduction of Confidence Levels for Transparent Network Planning
Introduction Confidence Levels Transparent Network Planning
2015/7/14
Confidence level on connection feasibilities is used to obtain Q-estimate margins when parameter uncertainties are considered. Adding such margins to the Q-estimate instead of fixed margins gives 22% ...
Nonlinear modeling with confidence estimation usingBayesian neural networks
Back-propagation neural network Bayesian neural network deep beams neural network
2009/2/19
There is a growing interest in the use of neural networks in civil engineering to model complicated nonlinearity problems. A recent enhancement to the conventional back-propagation neural network alg...
28 Feb 2007，(ROSSLYN, VA)—February was a healthy month for the electroindustry, and the future appears bright as well, according to senior industry executives responding to NEMA’s monthly Electroindus...
Enhance ASMs Based on AdaBoost-Based Salient Landmarks Localization and Confidence-Constraint Shape Modeling
Enhance ASMs AdaBoost-Based Salient Landmarks Localization
2010/12/15
Active Shape Model (ASM) has been recognized as one of the typical
methods for image understanding. Simply speaking, it iterates two steps:
profile-based landmarks local searching, and statistics-ba...