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A novel multiclass classification based approach for playback attack detection in speaker verification systems
Spoofing detection in automatic speaker verification (ASV) systems is typically handled as a binary classification approach. In this paper, we...
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GT-Net: global transformer network for multiclass brain tumor classification using MR images
Multiclass classification of brain tumors from magnetic resonance (MR) images is challenging due to high inter-class similarities. To this end,...
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Genetic Clustering Algorithm-Based Feature Selection and Divergent Random Forest for Multiclass Cancer Classification Using Gene Expression Data
Computational identification and classification of clinical disorders gather major importance due to the effective improvement of machine learning...
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Hybrid intelligent predictive maintenance model for multiclass fault classification
Data recorded from monitoring the health condition of industrial equipment are often high-dimensional, nonlinear, nonstationary and characterised by...
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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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Wireless capsule endoscopy multiclass classification using three-dimensional deep convolutional neural network model
BackgroundWireless capsule endoscopy (WCE) is a patient-friendly and non-invasive technology that scans the whole of the gastrointestinal tract,...
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A Novel Approach for Multiclass Brain Tumour Classification in MR Images
Brain tumours are now one of the leading causes of mortality across all forms of cancer. MRI is the most frequently used tool for identifying brain...
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Multiclass Classification Fault Diagnosis of Multirotor UAVs Utilizing a Deep Neural Network
A fault diagnosis algorithm using a deep neural network for an octocopter Unmanned Aerial Vehicle (UAV) is proposed. All eight rotors are considered...
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Liver Cirrhosis Stage Prediction Using Machine Learning: Multiclass Classification
Liver cirrhosis is a disease that affects a large population worldwide. Liver cirrhosis is further divided into four stages. This paper aims to...
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Multiclass Hierarchical Fuzzy Classification on Multi-labeled Data
Multiclass classification is dissimilar from binary classification based on the number of output classes. It can be implemented by using subsequent...
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Classification based on sparse representations of attributes derived from empirical mode decomposition in a multiclass problem of motor imagery in EEG signals
PurposeThe non-stationary nature of the EEG signal poses challenges for the classification of motor imagery. Sparse Representation Classification...
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A Multiclass Classification Approach for IoT Intrusion Detection Based on Feature Selection and Oversampling
Security of IoT networks is extremely necessary nowadays especially due to the rise of intrusion attacks in IoT networks that are not easily detected...
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Deep Learning Approach for IOT-Based Multiclass Weed Classification Using YOLOv5
The quality information about soil, local climate, and the crop in an IOT environment is captured by the sensors. Furthermore, it is possible to...
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Agglomeration of deep learning networks for classifying binary and multiclass classifications using 3D MRI images for early diagnosis of Alzheimer’s disease: a feature-node approach
Alzheimer’s disease is a degenerative brain condition causing memory loss in the elderly. Existing machine learning methods often yield low...
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Classifying multiclass relationships between ASes using graph convolutional network
Precisely understanding the business relationships between autonomous systems (ASes) is essential for studying the Internet structure. To date, many...
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Online Social Network Post Classification: A Multiclass approach
This paper presents the results of automating the process of social network posts’ two-level hierarchical (ensemble) classification. The research...
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Hybrid Contractive Auto-encoder with Restricted Boltzmann Machine For Multiclass Classification
Contractive auto-encoder (CAE) is a type of auto-encoders and a deep learning algorithm that is based on multilayer training approach. It is...
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A Novel Weighted Extreme Learning Machine for Highly Imbalanced Multiclass Classification
Baldota, Siddhant Aggarwal, DeeptiImbalance of classes in data distributions has proved to be a hindrance for their accurate classification. Remedies...
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Multiclass Image Classification Using OAA-SVM
Automatic image classification is a fundamental application of computer vision and machine learning. It employs feature extraction and...
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Cough Audio Signal-Based Clinical Emergency Classification of Corona Variant Infected Patients Using Multiclass SVM
The variants of coronavirus both delta and omicron are much more contagious and affecting greater percentage of human population. In this research,...