CAT-Net: Convolution, attention, and transformer based network for single-lead ECG arrhythmia classification by Md Rabiul Islam (6424796)

“…CAT-Net establishes new benchmarks, achieving 99.14% overall accuracy and 94.69% macro F1 score on 5-class arrhythmia classification in the MIT-BIH dataset and 99.58% accuracy with 96.15% macro F1 score for 3-class classification in the INCART dataset.…”

Hybrid model for precise hepatitis-C classification using improved random forest and SVM method by Umesh Kumar Lilhore (17727684)

Suspicious Behavior Detection with Temporal Feature Extraction and Time-Series Classification for Shoplifting Crime Prevention by Nazir, Amril

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Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition by Tuffaha, Mohammed

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Heartbeat Abnormality Detection in Phonocardiogram Signals using Wavelet Time Scattering and Optimized KNN Classification by Tiwari, Shamik

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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

Subjects: “…Learning management system Neural network algorithms Systematic review Text classification Virtual learning environment…”
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Knowledge Fusion by Harnessing Support Vector Machines for Collaborative Uncertain Data Classification in Multiagent Systems by Hussein, Ahmad MohdAziz

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Robust Polynomial Classifier Using L1-norm minimization by Assaleh, Khaled

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Synthetic Leakage Current Data Generation for Machine Learning-Based Pollution Classification in High Voltage Insulators by unknown

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

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Defined Clinical Classifications Are Associated with Outcome of Patients with Anatomically Resectable Pancreatic Adenocarcinoma Treated with Neoadjuvant Therapy by Tzeng, Ching-Wei

“…Background We previously introduced a classification system for patients with localized pancreatic adenocarcinoma that integrates assessments of tumor anatomy, cancer biology, and patient physiology. …”
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Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques by Amith Khandakar (14151981)

“…The multilayer perceptron (MLP) classifier along with the features extracted from thermogram images showed an accuracy of 90.1% in multi-class classification, which outperformed the literature-reported performance metrics on this dataset.…”

An Integrated Design for Classification and Localization of Diabetic Foot Ulcer Based on CNN and YOLOv2-DFU Models by Javaria Amin (14557730)

“…In the classification phase, deep features are extracted and supplied to the number of classifiers such as KNN, DT, Ensemble, softmax, and NB to analyze the classification results for the selection of best classifiers. …”

A Convolutional Neural Network-Based Framework for Classification of Protein Localization Using Confocal Microscopy Images by Sonam Aggarwal (16904763)

Subjects: “…Human protein atlas image classification…”

LncRNA-Based Classification of Triple Negative Breast Cancer Revealed Inherent Tumor Heterogeneity and Vulnerabilities by Radhakrishnan Vishnubalaji (3563306)

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Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…In the present article, we proposed a novel transfer learning-based predictor called, Lung-EffNet for lung cancer classification. Lung-EffNet is built based on the architecture of EfficientNet and further modified by adding top layers in the classification head of the model. …”

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

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A Survey on Hybrid Free Space Optical and Radio Frequency Systems: Classification, Progress, Observations, and Challenges by Heyam Hassan (22466887)

“…This survey paper provides a comprehensive overview of hybrid FSO/RF systems, presenting a classification framework of the different hybrid setups proposed in the literature, and identifying the main design objectives of hybrid FSO/RF systems. …”

EEG-Based Semantic Vigilance Level Classification Using Directed Connectivity Patterns and Graph Theory Analysis by Yahya, Fares

“…The strength and directionality of information flow in the connectivity network by RWTE/PDC and the GTA measures significantly decrease with vigilance decrement, p<0.05. The classification results show that the proposed methods outperform other related and competitive methods available in the literature and achieve 100% accuracy in subject-dependent and above 89% in subject-independent level in each of the four frequency bands. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

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