Kishor Datta Gupta

University of Memphis, North Carolina A&T University, Lamar University
0000-0001-6867-2653
https://scholar.google.com/citations?user=yFREujoAAAAJ&hl=en
Publications42
h-index6
Citations240
Highly Influential Citations9
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  • Publications
  • Influence
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
TLDR
A deep learning-based model is developed that can detect COVID-19 patients with better accuracy both on CT scan and chest X-ray image dataset and test results demonstrate that it is conceivable to interpret top features that should have worked to build a trust AI framework to distinguish between patients with CO VID-19 symptoms with other patients.
A survey of blockchain from security perspective
TLDR
This survey examines the security issues of blockchain model related technologies and their applications based on a survey from recent research papers and shows which way blockchain development trends are going.
Leveraging Machine Learning Approach to Setup Software-Defined Network(SDN) Controller Rules During DDoS Attack
TLDR
A machine learning based Distributed Denial of Service (DDoS) attack detection system, implemented in a virtual SDN environment testbed, showed up to 93% detection accuracy with a low false-positive rate.
Extending the Storage Capacity And Noise Reduction of a Faster QR-Code
TLDR
A faster QR code which has more storage and can scan faster is proposed, which takes twice the time than normal QR code but it can also store double QR code data and is as faster as other QR code scanning technique.
COVID-19 Symptoms Detection Based on NasNetMobile with Explainable AI Using Various Imaging Modalities
TLDR
Results demonstrate that the proposed models can identify the infectious regions and top features; ultimately, it provides a potential opportunity to distinguish between COVID-19 patients with others.
Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance
TLDR
CART, along with RS or QT, outperforms all other ML algorithms with 100% accuracy, 100% precision, 99% recall, and 100% F1 score, and the study outcomes demonstrate that the model’s performance varies depending on the data scaling method.
A Review on Comparative Remarks, Performance Evaluation and Improvement Strategies of Quadrotor Controllers
TLDR
A thorough analysis of the current literature on the effects of multiple controllers on quadrotors, focusing on two separate approaches: controller hybridization and controller development are conducted.
Stylometry as a Reliable Method for Fallback Authentication
TLDR
This paper proposed to detect differences between writings on the same topic provided by a set of users and tested whether these differences are enough to use for an authentication system and observed that the combination of textual features can support authenticity of the user.
Detect Review Manipulation by Leveraging Reviewer Historical Stylometrics in Amazon, Yelp, Facebook and Google Reviews
TLDR
This paper provides a historical stylometry based methodology to detect review manipulations and supported that with results from Amazon, Yelp, Google, and Facebook.
A Robust Approach of Facial Orientation Recognition from Facial Features
TLDR
An image mapping technique for face analysis in smart camera networks with a feature extraction and data from the facial feature to obtain a set of facial structures which can work as landmarks for tracking and recognition of facial expressions.
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