Search Results for author:
Found 10 papers, 5 papers with code
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.
Transfer learning and Local interpretable model agnostic based visual approach in Monkeypox Disease Detection and Classification: A Deep Learning insights
The recent development of Monkeypox disease among various nations poses a global pandemic threat when the world is still fighting Coronavirus Disease-2019 (COVID-19).
Negative Selection Approach to support Formal Verification and Validation of BlackBox Models' Input Constraints
This paper investigates a meta-heuristic approach to search for unsafe candidate sub-requirements in partitioned input space.
Mitigating shortage of labeled data using clustering-based active learning with diversity exploration
In this paper, we proposed a new clustering-based active learning framework, namely Active Learning using a Clustering-based Sampling (ALCS), to address the shortage of labeled data.
Negative Selection Algorithm Research and Applications in the last decade: A Review
The Negative selection Algorithm (NSA) is one of the important methods in the field of Immunological Computation (or Artificial Immune Systems).
Study of Different Deep Learning Approach with Explainable AI for Screening Patients with COVID-19 Symptoms: Using CT Scan and Chest X-ray Image Dataset
It is necessary to conduct an initial screening of patients with the symptoms of COVID-19 disease to control the spread of the disease.
CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space
To address these issues, in this paper, we propose an approach to extract a very small number of aggregated features that are easy to interpret and compute, and empirically show that we obtain high prediction accuracy even with a significantly reduced feature-space.
Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks
Accordingly, we first used a diverse set of attack methods including adaptive attack methods (on our defense) to generate adversarial samples from the clean dataset.
Detect Review Manipulation by Leveraging Reviewer Historical Stylometrics in Amazon, Yelp, Facebook and Google Reviews
Consumers now check reviews and recommendations before consuming any services or products.
Faster High Density Monochromic QR-Codes with Reduced Error Rate
In our process, we used only black and white color to print in each bit module and from the percentage of area covered we deducted the level of color percentage despite positions of color bits in that module which increased its scanning speed and also reduced noise error rate to less than 10 percent
