feature based multiple models
Feature-based multiple models improve classification of mutation-induced stability changes
... mutations based on the accessible surface area or secondary struc- ...employing feature selection, we built specialised feature-based multiple models, each dedicated to a ...
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Neural legal judgment prediction in English
... neural models we considered outperform pre- vious feature-based models, but provide no jus- tification for their ...and multiple languages, to gain a broader perspective of their ...
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Efficient and Accurate Methods for Updating Generalized Linear Models with Multiple Feature Additions
... (or feature sets) are predictive of the final ...the feature sets. When a feature set is selected, we update the current model using the different updating ...LogitGOMP based on these ...
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Feature based Lucas Kanade and Active Appearance Models
... Scale-Invariant Feature Transform (SIFT) [34], Image Gradient Orientation kernel (IGO) [15], [20], Edge Structure (ES) [22], Local Binary Patterns (LBP) [35]–[37] with variations [38], and Gabor filters ...on ...
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Multiple Trajectories Feature Detection Technology Based on Data Mining
... are based on static analysis of PE ...signature based detecting methods run malware programs in virtual environment, and monitor the behavior of these programs to get their behavior ...detecting ...
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Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
... sparse models based on the information theoretic Minimum Description Length (MDL) ...the feature space by using two-part MDL coding schemes. We present MIC based models for the problems ...
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Deep Learning Based Sentiment Analysis for Recommender System
... learning models were widely used in the field of pattern recognition and image ...learning models are widely used to perform Natural Language Processing ...with multiple levels of nonlinear neural ...
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Spatio-Temporal Graphical-Model-Based Multiple Facial Feature Tracking
... utilized multiple cues to track ...shape/texture models; however they didn’t track both si- ...facial feature—mouth—was ...track multiple facial features rather than one facial fea- ...
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Neural Legal Judgment Prediction in English
... neural models we considered outperform pre- vious feature-based models, but provide no jus- tification for their ...and multiple languages, to gain a broader perspective of their ...
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Context Modeling based on Feature Models Expressed as Views on Ontologies via Mappings
... use feature modeling as a technique for context modeling and development of context-aware self-adaptive systems in order to improve reusability and new ...A feature model (FM), firstly proposed by Kang et ...
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A feature-based framework for semantic interoperability of product models
... product models in product ...Form Feature (DIFF) model as the representation o f features in the shape model along with an ontology that captures the vocabulary in use in feature ...extract ...
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Gabor feature based classification using statistical models for face recognition
... important feature selection algorithms in appearance based methods ...LDA based approaches first use the PCA to project an image into a lower dimensional space or so called face space, and then ...
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An analysis of content free dialogue representation, supervised classification methods and evaluation metrics for meeting topic segmentation
... Two aspects are essential for content-free topic segmentation: classification method and feature set selection. I study these two aspects separately and introduce clas- sification schemes in this section. ...
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A feature selection method based on multiple kernel learning with expression profiles of different types
... With the development of high-throughput microarray chip and RNA sequencing technology, we can obtain a large number of expression data with different types. The researchers can acquire these data from several public ...
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Dynamic Switching State Systems for Visual Tracking
... cycle. Based on the above drawn connections between the Bayesian perspective and the RNN perspective, for both on-line estimation tasks of recursive Bayesian fil- ters, there exists an RNN counterpart, where ...
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A Multimodal Approach to Biometric Recognition
... It is often observed that different classifiers with essentially the same overall accuracy misclassify different test patterns. In decision level fusion, each classifier operating under a binary hypothesis, applies a ...
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Advanced Content Based Image Retrieval Using Multiple Feature Extraction
... ABSTRACT:Due to the enormous increase inimage database sizes, as well as its vast deployment in various applications, many Content Based Image Retrieval (CBIR) systems have been developed. The challenge, however, ...
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Node-Based Learning of Multiple Gaussian Graphical Models
... We consider the problem of estimating high-dimensional Gaussian graphical models cor- responding to a single set of variables under several distinct conditions. This problem is motivated by the task of recovering ...
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Research on Gesture Recognition Based on Improved GBMR Segmentation and Multiple Feature Fusion
... algorithm based on motion information and the algorithm based on appearance feature ...is based on the assumption that the color of foreground and background is ob- viously different, so it is ...
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Complementary human detection and multiple feature based tracking using a stereo camera
... In the tracking phase, we distribute particles for per- sons initially detected. Each particle transits its state based on the predicted position of the target in the cur- rent frame. The likelihood of each ...
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