activity
20202023
most citedStudy of Different Deep Learning Approach with Explainable AI for Screening Patients with COVID-19 Symptoms: Using CT Scan and Chest X-ray Image Dataset

98 citations · 175 across the 10 of their papers we have counts for

collaborators

10 papers

eess.IV2023★ 3 cited

Introduction of Medical Imaging Modalities

S. K. M Shadekul Islam, MD Abdullah Al Nasim, Ismail Hossain +3

The diagnosis and treatment of various diseases had been expedited with the help of medical imaging. Different medical imaging modalities, including X-ray, Computed Tomography (CT)…

cs.CR2023

Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection

Mst Shapna Akter, Hossain Shahriar, Sheikh Iqbal Ahamed +6

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 prob…

eess.IV2022★ 9 cited

Transfer learning and Local interpretable model agnostic based visual approach in Monkeypox Disease Detection and Classification: A Deep Learning insights

Md Manjurul Ahsan, Tareque Abu Abdullah, Md Shahin Ali +4

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). At its dawn,…

cs.LG2022

Negative Selection Approach to support Formal Verification and Validation of BlackBox Models' Input Constraints

Abdul-Rauf Nuhu, Kishor Datta Gupta, Wendwosen Bellete Bedada +4

Generating unsafe sub-requirements from a partitioned input space to support verification-guided test cases for formal verification of black-box models is a challenging problem for…

cs.LG2022★ 2 cited

Mitigating shortage of labeled data using clustering-based active learning with diversity exploration

Xuyang Yan, Shabnam Nazmi, Biniam Gebru +4

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 dat…

cs.CR2021★ 1 cited

Who is Responsible for Adversarial Defense?

Kishor Datta Gupta, Dipankar Dasgupta

We have seen a surge in research aims toward adversarial attacks and defenses in AI/ML systems. While it is crucial to formulate new attack methods and devise novel defense strateg…

cs.NE2021★ 34 cited

Negative Selection Algorithm Research and Applications in the last decade: A Review

Kishor Datta Gupta, Dipankar Dasgupta

The Negative selection Algorithm (NSA) is one of the important methods in the field of Immunological Computation (or Artificial Immune Systems). Over the years, some progress was m…

eess.IV2020★ 98 cited

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

Md Manjurul Ahsan, Kishor Datta Gupta, Mohammad Maminur Islam +3

The outbreak of COVID-19 disease caused more than 100,000 deaths so far in the USA alone. It is necessary to conduct an initial screening of patients with the symptoms of COVID-19…

cs.CV2020★ 9 cited

Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks

Kishor Datta Gupta, Zahid Akhtar, Dipankar Dasgupta

Developing secure machine learning models from adversarial examples is challenging as various methods are continually being developed to generate adversarial attacks. In this work,…

cs.CV2020★ 19 cited

CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space

Anik Khan, Kishor Datta Gupta, Deepak Venugopal +1

Predicting if red blood cells (RBC) are infected with the malaria parasite is an important problem in Pathology. Recently, supervised machine learning approaches have been used for…