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Do Prior Information on Performance of Individual Classifiers for Fusion of Probabilistic Classifier Outputs Matter?
In this paper, a class of classifier fusion methods are compared to verify the impact of the use of some prior information about individual...
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Group-Fusion One-Dimensional Convolutional Neural Network for Ballistic Target High-Resolution Range Profile Recognition with Layer-Wise Auxiliary Classifiers
Ballistic missile defense systems require accurate target recognition technology. Effective feature extraction is crucial for this purpose. The deep...
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Automotive Clutch Fault Diagnosis Through Feature Fusion and Lazy Family of Classifiers
BackgroundThe clutch is an indispensable component within the automotive system, facilitating the transfer of engine power to essential drive...
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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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MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder
BackgroundIntegrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative...
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Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques
The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visible tongue images with various fusion rules of...
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Ensemble Decision Fusion of Deep Learning Classifiers for Heart Disease Classification
Earlier detection of heart disease has gained wide research interest due to its higher mortality and challenges its accurate prediction....
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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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Hybrid Classifier for Optimizing Mental Health Prediction: Feature Engineering and Fusion Technique
A major worldwide health concern is mental health issues, which highlights the importance of early identification and intervention. In this paper,...
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On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers
An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking...
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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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Speech emotion classification using feature-level and classifier-level fusion
AbstractEmotion plays a vital role in every living being. Understanding emotion is a very complex task for everyone, but if possible, it will work...
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Multiple classifiers fusion for facial expression recognition
Human facial expression recognition has been treated as a multi-class classification problem in the field of artificial intelligence. The main...
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Sarcopenia prediction using shear-wave elastography, grayscale ultrasonography, and clinical information with machine learning fusion techniques: feature-level fusion vs. score-level fusion
This study aimed to develop and evaluate a sarcopenia prediction model by fusing numerical features from shear-wave elastography (SWE) and gray-scale...
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Ensemble Subspace Discriminant Classifiers for Misalignment Fault Classification Using Vibro-acoustic Sensor Data Fusion
BackgroundMisalignment is one of the major reasons for rotating machinery breakdown. Conventionally, misalignment diagnosis is done by the occurrence...
