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An approach of classifiers fusion based on hierarchical modifications
Classifiers fusion is considered as an effective way to promote the accuracy of pattern recognition. In practice, its performance is mainly limited...
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Permutation-invariant linear classifiers
Invariant concept classes form the backbone of classification algorithms immune to specific data transformations, ensuring consistent predictions...
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A geometric framework for multiclass ensemble classifiers
Ensemble classifiers have been investigated by many in the artificial intelligence and machine learning community. Majority voting and weighted...
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Decision fusion for few-shot image classification
Recent few-shot learning methods mostly only use a single classifier to complete image classification. In general, a single classifier is likely to...
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An ensemble pruning method considering classifiers’ interaction based on information theory for facial expression recognition
Ensemble learning combines all generated base learners for better generalization performance, but weak and redundant classifiers reduce the...
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Data fusion and network intrusion detection systems
The increasing frequency and sophistication of cyber-attacks pose significant threats to organizational entities and critical national...
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Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning
Quantification is a supervised Machine Learning task that estimates the class distribution in an unlabeled test set. Quantification has practical...
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Amelioration of multitudinous classifiers performance with hyper-parameters tuning in elephant search optimization for cardiac arrhythmias detection
Detecting cardiac abnormalities promptly is critical for preventing unexpected and premature fatalities. In this research, four types of cardiac...
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CCA-Based Fusion of Camera and Radar Features for Target Classification Under Adverse Weather Conditions
Deep learning models such as deep convolutional neural networks (DCNNs) image classifiers have achieved outstanding performance over the last decade....
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Speech emotion recognition using multimodal feature fusion with machine learning approach
Speech-based emotional state recognition must have a significant impact on artificial intelligence as machine learning advances. When it comes to...
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Machine learning approach of speech emotions recognition using feature fusion technique
In advancement of machine learning aspect, speech based emotional states identification must have a profound impact on artificial intelligence....
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Text-Independent Speaker Recognition System Using Feature-Level Fusion for Audio Databases of Various Sizes
To improve the speaker recognition rate, we propose a speaker recognition model based on the fusion of different kinds of speech features. A new type...
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Investigation of Scalograms with a Deep Feature Fusion Approach for Detection of Parkinson’s Disease
Parkinson’s disease (PD) is a neurological condition that millions of people worldwide suffer from. Early symptoms include a slight sense of weakness...
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Ensemble learning based-features extraction for brain mr images classification with machine learning classifiers
In general, different neuroimaging methods including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography...
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Information Fusion Based on Score/Weight Classifier Fusion
By applying different classifiers to the classification, multiple classification scores will be generated. Generally, different classifiers enjoy...
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Fusion of Multiple Classifiers Using Self Supervised Learning for Satellite Image Change Detection
Deep learning methods are widely used in the domain of change detection in remote sensing images. While datasets of that kind are abundant, annotated...
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Improving recognition of deteriorated historical Persian geometric patterns by fusion decision methods
Historical architecture has different special styles attributed to each era, dynasty, or region. These styles are common features such as geometric...
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Ear recognition with ensemble classifiers; A deep learning approach
Biometrics has emerged as a major domain for security systems. Ear as a biometric has many distinctive features which makes it promising for personal...
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Exploring the potential of Wav2vec 2.0 for speech emotion recognition using classifier combination and attention-based feature fusion
AbstractSelf-supervised learning models, such as Wav2vec 2.0, extract efficient features for speech processing applications including speech emotion...
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Fully connected network samples transfer and multi-classifier fusion for motor imagery recognition
In the field of motor imagery (MI) recognition, there are two problems, which are poor generalization and low recognition performance. A method of MI...
