A deep learning based artificial neural network approach for intrusion detection
SS Roy, A Mallik, R Gulati, MS Obaidat… - … and Computing: Third …, 2017 - Springer
Security of data is considered to be one of the most important concerns in today's world.
Data is vulnerable to various types of intrusion attacks that may reduce the utility of any …
Data is vulnerable to various types of intrusion attacks that may reduce the utility of any …
L2 regularized deep convolutional neural networks for fire detection
SS Roy, V Goti, A Sood, H Roy… - Journal of Intelligent …, 2022 - content.iospress.com
Fire calamity is one of the worst adversarial events that can happen to the human race. Fire
disaster can happen as a manmade disaster or even naturally, and it may cause …
disaster can happen as a manmade disaster or even naturally, and it may cause …
Natural language generation using sequential models: a survey
Abstract Natural Language Generation (NLG) is one of the most critical yet challenging tasks
in all Natural Language Processing applications. It is a process to automate text generation …
in all Natural Language Processing applications. It is a process to automate text generation …
Email-Based cyberstalking detection on textual data using Multi-Model soft voting technique of machine learning approach
In the virtual world, many internet applications are used by a mass of people for several
purposes. Internet applications are the basic needs of people in the modern days of lifestyle …
purposes. Internet applications are the basic needs of people in the modern days of lifestyle …
A deep learning based CNN approach on MRI for Alzheimer's disease detection
SS Roy, R Sikaria, A Susan - Intelligent Decision …, 2019 - content.iospress.com
Alzheimer's disease is a brain disorder which causes the malfunction of neurons. This
disease can cause loss of brain function and dementia which can further damage memory …
disease can cause loss of brain function and dementia which can further damage memory …
Research on intrusion detection based on KPCA-BP neural network
D Hongwei, W Liang - 2018 IEEE 18th International …, 2018 - ieeexplore.ieee.org
In view of the traditional BP neural network, high-dimensional complex data is prone to slow
detection rate and low accuracy in network intrusion detection. To reduce data dimension …
detection rate and low accuracy in network intrusion detection. To reduce data dimension …
Spam email detection using deep support vector machine, support vector machine and artificial neural network
Emails are a very important part of our life today for information sharing. It is used for both
personal communication as well as business purposes. But the internet also opens up the …
personal communication as well as business purposes. But the internet also opens up the …
Classifying multi-category images using deep learning: a convolutional neural network model
A Bandhu, SS Roy - … Recent Trends in Electronics, Information & …, 2017 - ieeexplore.ieee.org
This paper presents an image classification model using a convolutional neural network with
Tensor Flow. Tensor Flow is a popular open source library for machine learning and deep …
Tensor Flow. Tensor Flow is a popular open source library for machine learning and deep …
A novel approach for spam detection using natural language processing with AMALS models
To enhance their company operations, organizations within the industry leverage the
ecosystem of big data to manage vast volumes of information effectively. To achieve this …
ecosystem of big data to manage vast volumes of information effectively. To achieve this …
Deep learning for brain computer interfaces
From playing games with just the mind to capturing and re-constructing dreams, Brain
computer Interfaces (BCIs) have turned fiction into reality. It has set new standards in the …
computer Interfaces (BCIs) have turned fiction into reality. It has set new standards in the …