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FEATURE VECTOR CONSTRUCTION METHOD FOR IRIS RECOGNITION
Iris recognition Iris feature extraction Biometrics Mobile biometrics Quantization Encoding
2017/6/19
One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent compa...
Deep Learning of Feature Representation with Multiple Instance Learning for Medical Image Analysis
deep learning feature learning supervised un- supervised multiple instance learning
2016/1/22
This paper studies the effectiveness of accomplishing high-level tasks with a minimum of manual annotation and good feature rep-resentations for medical images. In medical image analysis, objects like...
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 ...
An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
slow feature analysis nonlinear blind source separation independent component analysis
2015/7/15
We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of ...
Empirical learning aided by weak domain knowledge in the form of feature importance
neural network domain knowledge prior knowledge feature importance
2015/7/15
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowledge while being cost ...
How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis
Slow feature analysis feature extraction classifi cation regression pattern recognition training graphs nonlinear dimensionality reduction supervised learning high-dimensional data implicitly supervised image analysis
2015/7/10
Supervised learning from high-dimensional data, e.g., multimedia data, is a challenging task. We propose an extension of slow feature analysis (SFA) for supervised dimensionality reduction called grap...
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 re nement for improved vortex resolution in aerodynamics ow elds. 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 re nement (AMR). Methods based on eigenvalues of the velocity gradient, di er...
Speech Feature Denoising and Dereverberation via Deep Autoencoders for Noisy Reverberant Speech Recognition
robust speech recognition feature denoising denoising autoencoder deep neural network
2014/11/27
Denoising autoencoders (DAs) have shown success in generating robust features for images, but there has been limited work in applying DAs for speech. In this paper we present a deep denoising autoenco...
Evaluation of feature-based methods for automated network orientation
Orientation Automation Feature extraction Calibration
2014/7/30
Every day new tools and algorithms for automated image processing and 3D reconstruction purposes become available, giving the possibility to process large networks of unoriented and markerless images,...
Margin Emphasized Metric Learning and Its Application to Gabor Feature Based Face Recognition
face verification metric learning margin Gabor Labeled Faces in Wild
2013/7/24
In addressing side information based face recognition scenario, a new Margin Emphasized Metric Learning (MEML) method is proposed. As an improvement of previous metric learning, MEML defines a new obj...
Context Constrained Facial Landmark Localization Based on Discontinuous Haar-like Feature
facial landmark localization context constraints discontinuous Haar-like feature
2013/7/24
Facial landmark localization is well known as one of the bottlenecks in face recognition. This paper proposes a novel facial landmark localization method, which introduces facial context constrains in...
Recognizing realistic action using contextual feature gr oup
Action recognition Spatial-temporal local feature Local feature group Discriminate group distance Mahalanobis distance
2013/7/24
Although the spatial-temporal local features and the bag of visual words model (BoW) have achieved a great success and a wide adoption in action classification, there still remain some problems. Fir...
Affective Video Classification Based on Spatio-Temporal Feature Fusion
video clssification facial expression recognition spatio-temporal feature fusion hidden dynamic conditional random fields
2013/7/24
In this paper, we propose a novel affective video classification method based on facial expression recognition by learning the spatio-temporal feature fusion of actors’ and viewers’ facial expressions...