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Fusion
Fusion has emerged as an important aspect of information processing in several very different fields. This chapter addresses the question of...
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Diagnosing Faults in Suspension System Using Machine Learning and Feature Fusion Strategy
Comfort and safety in automobiles can be enhanced with predictive maintenance by means of early problem detection and isolation, collectively...
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Multiclass skin lesion classification using deep learning networks optimal information fusion
A serious, all-encompassing, and deadly cancer that affects every part of the body is skin cancer. The most prevalent causes of skin lesions are UV...
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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...
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Multimodal Kernel-based discriminant correlation analysis data-fusion approach: an automated autism spectrum disorder diagnostic system
Autism spectrum disorder (ASD) diagnostic systems, based on association of multimodal tools such as combination of Electroencephalogram (EEG) and...
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A novel framework based on the multi-label classification for dynamic selection of classifiers
Multi-classifier systems (MCSs) are some kind of predictive models that classify instances by combining the output of an ensemble of classifiers...
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An Artificial Intelligence-Based Approach for Automated Classification of Obstructive Sleep Apnea by Considering Multi-modal Feature Fusion Technique
Obstructive Sleep Apnea (OSA) is a crucial sleep-breath disorder often characterized by partial or complete cessation of airflow during sleep. The...
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Application of analysis of variance to determine important features of signals for diagnostic classifiers of displacement pumps
This paper presents the use of one-way analysis of variance ANOVA as an effective tool for ranking the features calculated from diagnostic signals...
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Optimizing HAR Systems: Comparative Analysis of Enhanced SVM and k-NN Classifiers
This research addresses the accuracy issues in IoT-based human activity recognition (HAR) applications, essential for health monitoring, elderly...
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Improving the robustness and stability of a machine learning model for breast cancer prognosis through the use of multi-modal classifiers
Breast cancer is a deadly disease with a high mortality rate among PAN cancers. The advancements in biomedical information retrieval techniques have...
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Enhanced user verification in IoT applications: a fusion-based multimodal cancelable biometric system with ECG and PPG signals
The core premise of cancelable biometrics lies in the creation of a distinct biometric template for every individual, which can be either canceled or...
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Tri-model classifiers for EEG based mental task classification: hybrid optimization assisted framework
The commercial adoption of BCI technologies for both clinical and non-clinical applications is drawing scientists to the creation of wearable devices...
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TFN-FICFM: sEMG-Based Gesture Recognition Using Temporal Fusion Network and Fuzzy Integral-based Classifier Fusion
Surface electromyography (sEMG)-based gesture recognition is a key technology in the field of human–computer interaction. However, existing gesture...
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An enhanced method of feature fusion techniques to diagnosis neonatal hyperbilirubinemia
Neonatal disorder is most common in newborn babies. It is due to the unusual activity of the baby's organs. Neonatal hyperbilirubinemia is familiar...
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Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy
This investigation aimed to assess the effectiveness of different classification models in diagnosing prostate cancer using a screening dataset...
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ML-KFHE: Multi-label Ensemble Classification Algorithm Exploiting Sensor Fusion Properties of the Kalman Filter
Despite the success of ensemble classification methods in multi-class classification problems, ensemble methods based on approaches other than...
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Robust fault diagnosis of a high-voltage circuit breaker via an ensemble echo state network with evidence fusion
Reliable mechanical fault diagnosis of high-voltage circuit breakers is important to ensure the safety of electric power systems. Recent fault...
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Enhancing Melanoma Skin Cancer Detection Through Feature Fusion of Pre-Trained Deep Convolutional Neural Network ResNet50 and Thepade Sorted Block Truncation Coding
Identifying melanoma skin cancer accurately and promptly is crucial for successfully applying treatment methods. While helpful, conventional methods...
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Visual transformer and deep CNN prediction of high-risk COVID-19 infected patients using fusion of CT images and clinical data
BackgroundDespite the globally reducing hospitalization rates and the much lower risks of Covid-19 mortality, accurate diagnosis of the infection...
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Cotton crop classification using satellite images with score level fusion based hybrid model
Accurate cotton images are significant component for surveiling cotton development and its precise control. A suitable technique for charting the...
