classifier Fusion
Classifier Fusion of Hyperspectral and Lidar Remote Sensing Data For Improvement of Land Cover Classification
... Multiple Classifier System (MCS), classifier ensembles and classifier ...specific fusion method. The resulting classifier is generally more accurate than any of the individual ...
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Classification of voice disorder in children with cochlear implantation and hearing aid using multiple classifier fusion
... Comparing Table 5 with Table 4 it is observed that after combining outputs of the classifiers, the final classification rates in all levels increase compared with isolated classifiers. To have better classification ...
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Survey on Android Malware Detection Using Multilevel Classifier Fusion
... proposed classifier fusion approach with static analysis based on Android permissions and source code based ...voting fusion method. The best fusion model achieved a better accuracy rate of ...
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DroidFusion: A Novel Multilevel Classifier Fusion Approach for Android Malware Detection
... novel classifier fusion approach based on a multilevel architecture that enables effective combination of machine learning algorithms for improved ...the fusion of ensemble learning algorithms for ...
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Multi-Classifier Fusion Strategy for Activity and Intent Recognition of Torso Movements
... best classifier that might not be adequate by ...are classifier fusion and classifier selection. Classifier fusion utilizes approaches such as averaging or majority voting to ...
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Robust biometric person identification using automatic classifier fusion of speech, mouth, and face experts
... For the proposed method, the following design criteria were taken into account. Information from the audio, mouth, and face signals are to be combined to perform closed-set person identi- fication. The fusion ...
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Protein secondary structure prediction with classifier fusion
... This algorithm uses 3 layers of neural networks simi- lar to PHD method but it uses dierent types of features such as position specic scoring matrices, PSIBLAST frequency prole, HMM and [r] ...
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Feature grouping-based multiple fuzzy classifier system for fusion of hyperspectral and LIDAR data
... the fusion of different information can produce a better understanding of the observed ...the fusion of light detection and ranging (LIDAR) and passive optical remote sensing data for classification of land ...
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Optimization of Ensemble based Decision using PSO
... The classifier outputs are often normalized to the [0,1] interval, and then named as support given by classifier to each class which is based on class-conditional posterior probabilities [21], ...based ...
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Heterogeneous Deep Model Fusion for Automatic Modulation Classification
... Keywords: Deep learning; automatic modulation classification; classifier fusion; convolutional.. 25.[r] ...
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A Classifier Ensemble of Binary Classifier Ensembles
... base classifier in ensemble almost always produces a better performing ...unstable classifier, so it is better to use it as a base classifier in an ...stable classifier is the one converge to ...
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Host Based Intrusion Detection System Based on Fusion of Classifier using K means Clustering
... information fusion? This is on account of that data contained in single information source is restricted by its particular perception, subsequently; consolidating various perceptions may encourage the far reaching ...
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A patient adapting heartbeat classifier using ECG morphology and heart beat interval features
... In order to improve performance, research attention has been directed to patient adaptive arrhythmia detection, i.e., the clas- sifier uses expert knowledge about a section of the recording under analysis to improve the ...
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Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier
... KELM classifier. At the decision level, a soft decision fusion scheme, namely logarithmic opinion pool (LOGP) rule, merged the probability outputs and assigned the final class ...specific fusion ...
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Learning To Deal With Little Or No Annotated Data
... Example: Error rates for a web classifier Page-based classifier Hyperlink-based classifier Combined classifier (equal votes) Supervised training 12.9 12.4 11.1 Co-training 6.2 11.6[r] ...
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Max-margin stacking with group sparse regularization for classifier combination
... one-versus-one [29] and one-versus-all [30] methods. In one-versus-one method, we train a binary SVM using only datapoints of two particular classes for each class pair. Test phase is done by a max-wins voting strategy, ...
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Predicting sentiment-mention associations in product reviews
... domain classifier where labeled data is ...Level Fusion technique (described in Section ...The Classifier Level Fusion technique (described in Section ...
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Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems
... score-based fusion schemes ought to be ...the fusion algorithm rarely made use of less reliable face data (see Table 5), and consequently the fusion results sport a limited improvement over speech ...
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Framework of Classification Algorithms
... ABSTRACT: Data mining is a standout amongst the most critical research areas in the field of computer science. Data mining systems are utilized for separating the hidden learning from the extensive databases. There are ...
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Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences
... AbstractClassifiers provide methods for learning internal StatisticalModels on train- ing data from different classes and for classifying new input sequences. The TrainSMBased- Classifier trains each of the ...
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