Search Results for author:
Found 16 papers, 1 papers with code
A Trustable LSTM-Autoencoder Network for Cyberbullying Detection on Social Media Using Synthetic Data
This paper proposes a trustable LSTM-Autoencoder Network for cyberbullying detection on social media using synthetic data.
BlockTheFall: Wearable Device-based Fall Detection Framework Powered by Machine Learning and Blockchain for Elderly Care
Falls among the elderly are a major health concern, frequently resulting in serious injuries and a reduced quality of life.
Feature Engineering-Based Detection of Buffer Overflow Vulnerability in Source Code Using Neural Networks
We have conducted a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information.
Autism Disease Detection Using Transfer Learning Techniques: Performance Comparison Between Central Processing Unit vs Graphics Processing Unit Functions for Neural Networks
Moreover, the performance of the neural network models in terms of accuracy increased on GPU compared to CPU.
Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection
Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems.
Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis
Based on our observations, both ML and QML models exhibit vulnerability to adversarial attacks.
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms
Our goal is to distinguish the performance between QNN and NN and to conduct the experiment, we develop two different models for QNN and NN by utilizing Pennylane for quantum and TensorFlow and Keras for traditional respectively.
Multi-class Skin Cancer Classification Architecture Based on Deep Convolutional Neural Network
Furthermore, we develop five different stacking models such as inceptionv3-inceptionv3, Densenet-mobilenet, inceptionv3-Xception, Resnet50-Vgg16, and stack-six for classifying the skin lesions and found that the stacking models perform poorly.
Deep Learning Approach for Classifying the Aggressive Comments on Social Media: Machine Translated Data Vs Real Life Data
This paper particularly worked on the Hindi, Bangla, and English datasets to detect aggressive comments and have shown a novel way of generating machine-translated data to resolve data unavailability issues.
Handwritten Word Recognition using Deep Learning Approach: A Novel Way of Generating Handwritten Words
We have also demonstrated the process of recognizing handwritten documents using the deep learning model.
Towards Unsupervised Learning based Denoising of Cyber Physical System Data to Mitigate Security Concerns
Due to the noisy dynamics and mobile environment, the sensor readings can be very noisy.
Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing
One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code.
A Novel IoT-based Framework for Non-Invasive Human Hygiene Monitoring using Machine Learning Techniques
People's personal hygiene habits speak volumes about the condition of taking care of their bodies and health in daily lifestyle.
Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection
The optimal use of DNN-based classifiers requires careful tuning of the hyper-parameters.
Malware Detection and Prevention using Artificial Intelligence Techniques
The comprehension of this synthesis shall help researchers for further research on malware detection and prevention using AI.
An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness
In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches.
