Search Results for author: Sonali Agarwal

Found 26 papers, 5 papers with code

A Decision Support System for Liver Diseases Prediction: Integrating Batch Processing, Rule-Based Event Detection and SPARQL Query

no code implementations10 Nov 2023 Ritesh Chandra, Sadhana Tiwari, Satyam Rastogi, Sonali Agarwal

Using this SWRL in the ontology for predicting different types of liver disease with the help of the Pellet and Drool inference engines in Protege Tools, a total of 615 records are taken from different liver diseases.

Disease Prediction Event Detection

Semantic rule Web-based Diagnosis and Treatment of Vector-Borne Diseases using SWRL rules

no code implementations8 Jan 2023 Ritesh Chandra, Sadhana Tiwari, Sonali Agarwal, Navjot Singh

Afterwards, Basic Formal Ontology (BFO), National Vector Borne Disease Control Program (NVBDCP) guidelines, and RDF medical data are used to develop ontologies for VBDs, and Semantic Web Rule Language (SWRL) rules are applied for diagnosis and treatment.

Optical Character Recognition Optical Character Recognition (OCR)

Forecasting COVID- 19 cases using Statistical Models and Ontology-based Semantic Modelling: A real time data analytics approach

no code implementations6 Jun 2022 Sadhana Tiwari, Ritesh Chandra, Sonali Agarwal

), we designed a set of rules using Semantic Web Rule Language and some mathematical models for dealing with COVID19 infected cases on an individual basis.

Decision Making Time Series Analysis

Impact of the composition of feature extraction and class sampling in medicare fraud detection

no code implementations3 Jun 2022 Akrity Kumari, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

Following this, the healthcare industry has seen a significant increase in fraudulent activities owing to increased insurance, and fraud has become a significant contributor to rising medical care expenses, although its impact can be mitigated using fraud detection techniques.

Dimensionality Reduction Fraud Detection

BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models

1 code implementation7 Dec 2021 Narinder Singh Punn, Sonali Agarwal

To accomplish such task, the models are required to be trained using huge amount of annotated or labelled data that highlights the region of interest with a binary mask.

Image Segmentation Self-Supervised Learning +1

Impact of Attention on Adversarial Robustness of Image Classification Models

no code implementations2 Sep 2021 Prachi Agrawal, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

Adversarial attacks against deep learning models have gained significant attention and recent works have proposed explanations for the existence of adversarial examples and techniques to defend the models against these attacks.

Adversarial Robustness Classification +1

Modality specific U-Net variants for biomedical image segmentation: A survey

no code implementations9 Jul 2021 Narinder Singh Punn, Sonali Agarwal

With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most widely utilized in biomedical image segmentation to address the automation in identification and detection of the target regions or sub-regions.

Image Segmentation Semantic Segmentation

Hate speech detection using static BERT embeddings

no code implementations29 Jun 2021 Gaurav Rajput, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

With increasing popularity of social media platforms hate speech is emerging as a major concern, where it expresses abusive speech that targets specific group characteristics, such as gender, religion or ethnicity to spread violence.

Hate Speech Detection Specificity +1

BERT-Based Sentiment Analysis: A Software Engineering Perspective

2 code implementations4 Jun 2021 Himanshu Batra, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

The paper presents three different strategies to analyse BERT based model for sentiment analysis, where in the first strategy the BERT based pre-trained models are fine-tuned; in the second strategy an ensemble model is developed from BERT variants, and in the third strategy a compressed model (Distil BERT) is used.

Recommendation Systems Sentiment Analysis +2

CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images

no code implementations13 Dec 2020 Narinder Singh Punn, Sonali Agarwal

In the present article, an automated deep learning based model, COVID-19 hierarchical segmentation network (CHS-Net) is proposed that functions as a semantic hierarchical segmenter to identify the COVID-19 infected regions from lungs contour via CT medical imaging using two cascaded residual attention inception U-Net (RAIU-Net) models.

Computed Tomography (CT) Specificity

Pinball-OCSVM for early-stage COVID-19 diagnosis with limited posteroanterior chest X-ray images

no code implementations16 Oct 2020 Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan

The performance of the proposed model is compared with conventional OCSVM and existing deep learning models, and the experimental results prove that the proposed model outperformed over state-of-the-art methods.

COVID-19 Diagnosis Medical Diagnosis

Face Mask Detection using Transfer Learning of InceptionV3

no code implementations17 Sep 2020 G. Jignesh Chowdary, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

In this paper, a transfer learning model is proposed to automate the process of identifying the people who are not wearing mask.

Image Augmentation Transfer Learning

Fruit classification using deep feature maps in the presence of deceptive similar classes

no code implementations12 Jul 2020 Mohit Dandekar, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

The objective of the present research is to address the challenge of classification of deceptively similar multi-granular objects with an ensemble approach thfat utilizes activations from multiple layers of CNN (deep features).

Classification General Classification

Enhanced Behavioral Cloning Based self-driving Car Using Transfer Learning

no code implementations11 Jul 2020 Uppala Sumanth, Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal

With the growing phase of artificial intelligence and autonomous learning, the self-driving car is one of the promising area of research and emerging as a center of focus for automobile industries.

Self-Driving Cars Transfer Learning

Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques

2 code implementations4 May 2020 Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal, Gaurav Rai

From the experimental analysis, it is observed that the YOLO v3 with Deepsort tracking scheme displayed best results with balanced mAP and FPS score to monitor the social distancing in real-time.

Human Detection object-detection +1

Target specific mining of COVID-19 scholarly articles using one-class approach

no code implementations24 Apr 2020 Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan

In recent years, several research articles have been published in the field of corona-virus caused diseases like severe acute respiratory syndrome (SARS), middle east respiratory syndrome (MERS) and COVID-19.

Clustering

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