Gulshan Kumar
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View article: Unmanned Aerial Vehicle-Based Road Damage Detection Using Convolutional Neural Networks
Unmanned Aerial Vehicle-Based Road Damage Detection Using Convolutional Neural Networks Open
Using images taken by unmanned aerial vehicles (UAVs) and deep learning algorithms, this study introduces a novel method for detecting road damage and cracks. Maintaining sturdy roadways depends on regularly inspecting and repairing street…
View article: PHISH-NET A Machine Learning Based Client-Side Defence Against Spoofing Attacks
PHISH-NET A Machine Learning Based Client-Side Defence Against Spoofing Attacks Open
Phishing attacks pose a significant cybersecurity threat, prompting the development of Phish Net, a client-side security solution that utilizes machine learning for real-time detection of phishing websites. Integrated as a Google Chrome ex…
View article: AutoETL: A Nonlinear Deep Learning Framework for ETL Automation
AutoETL: A Nonlinear Deep Learning Framework for ETL Automation Open
This study presents a nonlinear framework for automating Extract, Transform, Load (ETL) processes. The framework uses natural language processing techniques, transformer-based models, and reinforcement learning to convert unstructured data…
View article: Review of: "EEG-based Emotion Classification using Deep Learning: Approaches, Trends and Bibliometrics"
Review of: "EEG-based Emotion Classification using Deep Learning: Approaches, Trends and Bibliometrics" Open
Potential competing interests: No potential competing interests to
View article: A Comprehensive Review on Deep Learning Model for Multi Class Satellite Image Classification and Prediction
A Comprehensive Review on Deep Learning Model for Multi Class Satellite Image Classification and Prediction Open
Satellite images provide a wealth of information about the Earth's surface, but extracting meaningful insights from these vast datasets requires sophisticated analysis techniques. Deep learning models have emerged as powerful tools for mul…
View article: Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats
Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats Open
This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost, a machine learning algorithm renowned for its efficiency and performance. The framework proposed herein utilizes the…
View article: A modified grasshopper optimization algorithm based on levy flight for cluster head selection in wireless sensor networks
A modified grasshopper optimization algorithm based on levy flight for cluster head selection in wireless sensor networks Open
In recent years, technological advancements have enabled the use of wireless sensor networks (WSNs) for essential applications such as inventory tracking, health monitoring, remote sensing, seismic event monitoring, military surveillance, …
View article: Machine Learning Techniques for Intrusion Detection Systems in SDN-Recent Advances, Challenges and Future Directions
Machine Learning Techniques for Intrusion Detection Systems in SDN-Recent Advances, Challenges and Future Directions Open
Software-Defined Networking (SDN) enables flexibility in developing security tools that can effectively and efficiently analyze and detect malicious network traffic for detecting intrusions. Recently Machine Learning (ML) techniques have a…
View article: Analysis of Machine Learning Algorithms with Feature Selection for Intrusion Detection using UNSW-NB15 Dataset
Analysis of Machine Learning Algorithms with Feature Selection for Intrusion Detection using UNSW-NB15 Dataset Open
In recent times, various machine learning classifiers are used to improve network intrusion detection. The researchers have proposed many solutions for intrusion detection in the literature. The machine learning classifiers are trained on …
View article: Performance Analysis of Machine Learning Classifiers for Intrusion Detection using UNSW-NB15 Dataset
Performance Analysis of Machine Learning Classifiers for Intrusion Detection using UNSW-NB15 Dataset Open
With the advancement of internet technology, the numbers of threats are also rising exponentially. To reduce the impact of these threats, researchers have proposed many solutions for intrusion detection. In the literature, various machine …
View article: Cybercrimes: A Proposed Taxonomy and Challenges
Cybercrimes: A Proposed Taxonomy and Challenges Open
Cybersecurity is one of the most important concepts of cyberworld which provides protection to the cyberspace from various types of cybercrimes. This paper provides an updated survey of cybersecurity. We conduct the survey of security of r…
View article: Nature Inspired Feature Selection Approach for Effective Intrusion Detection
Nature Inspired Feature Selection Approach for Effective Intrusion Detection Open
Objectives: To reduce the dimensionality of network traffic dataset by selecting the relevant and irredundant features for accurate and quick intrusion detection. To achieve the target, we proposed a new feature selection approach based on…
View article: Denial of service attacks – an updated perspective
Denial of service attacks – an updated perspective Open
Network security is a specialized field consisting of the provisions and policies to prevent and monitor unauthorized access, misuse, modification or denial of a computer network and network-accessible resources as well as ensuring their a…