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Browsing BITS Faculty Publications by Author "Narang, Pratik"

Now showing items 1-20 of 37

AENeT: an attention-enabled neural architecture for fake news detection using contextual features

Narang, Pratik; Sharma, Yashvardhan (Springer, 2021)

In the current era of social media, the popularity of smartphones and social media platforms has increased exponentially. Through these electronic media, fake news has been rising rapidly with the advent of new sources ...
AI-Enabled Object Detection in UAVs: Challenges, Design Choices, and Research Directions

Narang, Pratik; Chamola, Vinay (IEEE, 2021-08)

Unmanned aerial vehicles (UAVs) are emerging as a powerful tool for various industrial and smart city applications. UAVs coupled with various sensors can perform many cognitive tasks such as object detection, surveillance, ...
AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges

Narang, Pratik; Narang, Pratik; Chamola, Vinay (Springer, 2021-03)

The COVID-19 pandemic has overwhelmed the existing healthcare infrastructure in many parts of the world. Healthcare professionals are not only over-burdened but also at a high risk of nosocomial transmission from COVID-19 ...
Anomaly detection in diurnal CPS monitoring data using a local density approach

Narang, Pratik (IEEE, 2016)

Devices that monitor and measure various system parameters or physical phenomena form an integral part of cyber-physical systems. Such devices usually operate continuously and gather important data that is often critical ...
Background Invariant Faster Motion Modeling for Drone Action Recognition

Narang, Pratik (MDPI, 2021-07)

Visual data collected from drones has opened a new direction for surveillance applications and has recently attracted considerable attention among computer vision researchers. Due to the availability and increasing use of ...
Deep3DSCan: Deep residual network and morphological descriptor based framework forlung cancer classification and 3D segmentation

Raman, Sundaresan; Chamola, Vinay; Narang, Pratik (IET, 2020-04)

With the increasing incidence rate of lung cancer patients, early diagnosis could help in reducing the mortality rate. However, accurate recognition of cancerous lesions is immensely challenging owing to factors such as ...
DeepFakE: improving fake news detection using tensor decomposition-based deep neural network

Narang, Pratik (Springer, 2020-05)

Social media platforms have simplified the sharing of information, which includes news as well, as compared to traditional ways. The ease of access and sharing the data with the revolution in mobile technology has led to ...
DerainGAN: Single image deraining using wasserstein GAN

Narang, Pratik (Springer, 2021-09)

Rainy weather greatly affects the visibility of salient objects and scenes in the captured images and videos. The object/scene visibility varies with the type of raindrops, i.e. adherent rain droplets, streaks, rain, ...
Domain-Aware Unsupervised Hyperspectral Reconstruction for Aerial Image Dehazing

Narang, Pratik (ARXIV, 2020)

Haze removal in aerial images is a challenging problem due to considerable variation in spatial details and varying contrast. Changes in particulate matter density often lead to degradation in visibility. Therefore, several ...
Downlink power control for latency aware grid energy savings in green cellular networks

Narang, Pratik; Chamola, Vinay (IEEE, 2016)

Mobile service providers can achieve cost savings by deploying Base Stations (BSs) which harvest renewable energy as they reduce the energy drawn from the grid and its associated cost. The cost savings can be further ...
Drone-surveillance for search and rescue in natural disaster

Narang, Pratik (Elsevier, 2020-04)

Due to the increasing capability of drones and requirements to monitor remote areas, drone surveillance is becoming popular. In case of natural disaster, it can scan the wide affected-area quickly and make the search and ...
DroneSegNet: Robust Aerial Semantic Segmentation for UAV-Based IoT Applications

Narang, Pratik; Chamola, Vinay (IEEE, 2022-04)

Unmanned Aerial Vehicles (UAVs) are the promising “Flying IoT” devices of the future, which can be equipped with various sensors and cognitive capabilities to perform numerous tasks related to remote sensing, search and ...
EchoFakeD: improving fake news detection in social media with an efficient deep neural network

Narang, Pratik (Springer, 2021-01)

The increasing popularity of social media platforms has simplified the sharing of news articles that have led to the explosion in fake news. With the emergence of fake news at a very rapid rate, a serious concern has ...
EraisNET: An Optical Flow based 3D ConvNET for Erasing Obstructions

Narang, Pratik; Rajput, Amitesh Singh (IEEE, 2022)

Images captured from behind a fence, window, or during rain generally face occlusions. Though prior works have addressed the problems of individually de-raining, reflection, and occlusion removal, a common approach that ...
FakeBERT: Fake news detection in social media with a BERT-based deep learning approach

Narang, Pratik (Springer, 2021-01)

In the modern era of computing, the news ecosystem has transformed from old traditional print media to social media outlets. Social media platforms allow us to consume news much faster, with less restricted editing results ...
Feature Selection for Detection of Peer-to-Peer Botnet Traffic

Narang, Pratik (ACM Digital Library, 2013)

The use of anomaly-based classification of intrusions has increased significantly for Intrusion Detection Systems. Large number of training data samples and a good ‘feature set’ are two primary requirements to build ...
FNDNet – A deep convolutional neural network for fake news detection

Narang, Pratik (Elsevier, 2020-06)

With the increasing popularity of social media and web-based forums, the distribution of fake news has become a major threat to various sectors and agencies. This has abated trust in the media, leaving readers in a state ...
Game-theoretic strategies for IDS deployment in peer-to-peer networks

Narang, Pratik (Springer, 2015-07)

This work studies the problem of optimal positioning of Intrusion Detection Systems (IDSs) in a Peer-to-Peer (P2P) environment involving a number of peers and super-peers. This scenario applies to network architectures ...
Hades: A Hadoopbased Framework for Detection of PeertoPeer Botnets

Narang, Pratik (ACM Digital Library, 2014)

This paper presents Hades, a Hadoop-based framework for detection of P2P botnets in an enterprise-level network, which is distributed and scalable by design. The contri- butions of this work are two-fold: Firstly, our ...
HIDeGan: A Hyperspectral-guided Image Dehazing GAN

Narang, Pratik (IEEE, 2020)

Haze removal in images captured from a diverse set of scenarios is a very challenging problem. The existing dehazing methods either reconstruct the transmission map or directly estimate the dehazed image in RGB color space. ...

Now showing items 1-20 of 37

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