6 papers
Quanvolutional Neural Networks for Pneumonia Detection: An Efficient Quantum-Assisted Feature Extraction Paradigm
Gazi Tanbhir, Md. Farhan Shahriyar, Abdullah Md Raihan Chy
Pneumonia poses a significant global health challenge, demanding accurate and timely diagnosis. While deep learning, particularly Convolutional Neural Networks (CNNs), has shown pr…
Quantum Machine Learning for Image Classification: A Hybrid Model of Residual Network with Quantum Support Vector Machine
Md. Farhan Shahriyar, Gazi Tanbhir, Abdullah Md Raihan Chy
Recently, there has been growing attention on combining quantum machine learning (QML) with classical deep learning approaches, as computational techniques are key to improving the…
Advancements and Challenges in Quantum Machine Learning for Medical Image Classification: A Comprehensive Review
Md Farhan Shahriyar, Gazi Tanbhir
Quantum technologies are rapidly advancing as image classification tasks grow more complex due to large image volumes and extensive parameter updates required by traditional machin…
Quantum-Inspired Privacy-Preserving Federated Learning Framework for Secure Dementia Classification
Gazi Tanbhir, Md. Farhan Shahriyar
Dementia, a neurological disorder impacting millions globally, presents significant challenges in diagnosis and patient care. With the rise of privacy concerns and security threats…
PhishVQC: Optimizing Phishing URL Detection with Correlation Based Feature Selection and Variational Quantum Classifier
Md. Farhan Shahriyar, Gazi Tanbhir, Abdullah Md Raihan Chy +2
Phishing URL detection is crucial in cybersecurity as malicious websites disguise themselves to steal sensitive infor mation. Traditional machine learning techniques struggle to pe…
Hybrid Machine Learning Model for Detecting Bangla Smishing Text Using BERT and Character-Level CNN
Gazi Tanbhir, Md. Farhan Shahriyar, Khandker Shahed +2
Smishing is a social engineering attack using SMS containing malicious content to deceive individuals into disclosing sensitive information or transferring money to cybercriminals.…