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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...
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...
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 ...
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 ...
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 ...
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...
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-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...
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...
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,...
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...
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...
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...
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...

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