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Using Feature Weights to Improve Performance of Neural Networks
Feature weight Feature ranking Hybrid Learning Correlation Constraint learning
2015/7/21
Different features have different relevance to a particular learning problem. Some features are less relevant; while some very important. Instead of selecting the most relevant features using feature ...
Combined Feature-Driven Richardson-Based Adaptive Mesh Refinement for Unsteady Vortical Flows
Combined Feature-Driven Richardson-Based Adaptive Mesh Unsteady Vortical Flows
2015/7/3
An adaptive mesh refinement strategy that couples feature detection with local error estimation is presented. The strategyfirst selects vortical regions for refinement using feature ...
Feature-Driven Cartesian Adaptive Mesh Refinement in the Helios Code
Feature-Driven Cartesian Adaptive Mesh Refinement Helios Code
2015/7/3
Feature-detection methods are applied to drive Cartesian-based adaptive mesh renement for improved vortex resolution in aerodynamics owelds. Several approaches such as the Q-criterion, the eigenvalu...
We investigate feature detection schemes used to guide appropriate mesh resolution for CFD calculations with adaptive mesh renement (AMR). Methods based on eigenvalues of the velocity gradient, dier...
SIFT BASED ALGORITHM FOR POINT FEATURE TRACKING
SIFT feature magnitude orientation descriptor
2010/1/11
In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighbor...