Muthu Subash Kavitha
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View article: REAL-TIME PCR DETECTION OF ANAPLASMA SPP. IN DROMEDARY CAMELS IN QATAR
REAL-TIME PCR DETECTION OF ANAPLASMA SPP. IN DROMEDARY CAMELS IN QATAR Open
In recent years, Qatar’s population has grown quickly, which has led to a rise in camels (Camelus dromedarius, one-humped). This increased the risk of infection. Six species of bacteria of the genus Anaplasma are responsible for the tick- …
View article: EXACT COMPUTATION OF ZAGREB-TYPE AND RANDIĆ INDICES IN COMPLEX NANOSTRUCTURED GRAPH MODELS
EXACT COMPUTATION OF ZAGREB-TYPE AND RANDIĆ INDICES IN COMPLEX NANOSTRUCTURED GRAPH MODELS Open
In the present work, we compute exact analytical expressions for certain degree-based topological indices, namely, Randić index Ra(G) for different values of , the first Zagreb index, the hyper Zagreb index, atom-bond connectivity (ABC) in…
View article: Optimized technique for the early identification of Parkinson's disease using machine learning-based handwriting and voice analysis
Optimized technique for the early identification of Parkinson's disease using machine learning-based handwriting and voice analysis Open
Movement impairments caused by Parkinson's disease include tremors and rigidity in the muscles. Due to the fact that each patient's symptoms are unique, PD can easily go undiagnosed. Because of this, the early phases of Parkinson's disease…
View article: <b>Tumor Growth Stage Prediction on Ultrasound Breast Cancer Images with Backpropagation Network</b><b></b>
<b>Tumor Growth Stage Prediction on Ultrasound Breast Cancer Images with Backpropagation Network</b><b></b> Open
Neural Networks are computational models for solving various complex problems. Systematic learning without user support for ultrasound-screened breast cancer images aims to predict the growth of the tumor. Even though technology is improvi…
View article: Real Time Anomaly Detection in Cybersecurity Using Generative Adversarial Networks and Autoencoders
Real Time Anomaly Detection in Cybersecurity Using Generative Adversarial Networks and Autoencoders Open
Anomaly detection was a critical aspect of cybersecurity, with the increasing complexity and volume of data posing significant challenges for traditional methods. This chapter explores the application of advanced deep learning techniques, …
View article: DEEP RESIDUAL NETWORKS FORIMAGE SUPER RESOLUTION FORIMPROVED IMAGE CLARITY
DEEP RESIDUAL NETWORKS FORIMAGE SUPER RESOLUTION FORIMPROVED IMAGE CLARITY Open
Image Super-Resolution (SR) is a crucial task in computer vision, aiming to enhance the resolution and clarity of low-resolution images. Deep Residual Networks (ResNets) have significantly improved SR performance by efficiently learning hi…
View article: Middle East respiratory syndrome coronavirus (MERS-CoV) internalization does not rely on DPP4 cytoplasmic tail signaling
Middle East respiratory syndrome coronavirus (MERS-CoV) internalization does not rely on DPP4 cytoplasmic tail signaling Open
Middle East respiratory syndrome coronavirus (MERS-CoV) infects respiratory epithelial cells in humans and camels by binding to dipeptidyl peptidase 4 (DPP4) as its entry receptor. DPP4 is a multifunctional type II membrane protein with a …
View article: Tea leaf disease detection using segment anything model and deep convolutional neural networks
Tea leaf disease detection using segment anything model and deep convolutional neural networks Open
Tea is an important beverage across many cultures. Diseases affecting tea leaves can adversely impact the integrity, production and cause substantial economic losses. Hence, detecting these diseases efficiently and accurately at an early s…
View article: Modelling Neutrosophic Agility Index: A Mathematical Framework
Modelling Neutrosophic Agility Index: A Mathematical Framework Open
Introduction: This study uses a fuzzy-based methodology that combines agility score and certainty functions to assess the values of learning mathematics quickly. The paper emphasises the need of understanding the value of learning mathemat…
View article: A Fractional-Order Mathematical Model of Banana Xanthomonas Wilt Disease Using Caputo Derivatives
A Fractional-Order Mathematical Model of Banana Xanthomonas Wilt Disease Using Caputo Derivatives Open
This article investigates a fractional-order mathematical model of Banana Xanthomonas Wilt disease while considering control measures using Caputo derivatives. The proposed model is numerically solved using the L1-based predictor-corrector…
View article: An Improved Normalized Difference Vegetation Index (NDVI) Estimation Using Grounded Dino and Segment Anything Model for Plant Health Classification
An Improved Normalized Difference Vegetation Index (NDVI) Estimation Using Grounded Dino and Segment Anything Model for Plant Health Classification Open
Ensuring sustainable and profitable agriculture is critical for addressing global food security challenges. This has resulted in the need for automation in plant health identification. However, this objective is hampered by the lack of eff…
View article: Fetal growth analysis from ultrasound videos based on different biometrics using optimal segmentation and hybrid classifier
Fetal growth analysis from ultrasound videos based on different biometrics using optimal segmentation and hybrid classifier Open
Birth defects and their associated deaths, high health and financial costs of maternal care and associated morbidity are major contributors to infant mortality. If permitted by law, prenatal diagnosis allows for intrauterine care, more com…
View article: A Novel Approach on Plithogenic Interval Valued Neutrosophic Hypersoft Sets and its Application in Decision Making
A Novel Approach on Plithogenic Interval Valued Neutrosophic Hypersoft Sets and its Application in Decision Making Open
<div>\n<h2>Abstract</h2>\n<p><strong>Objectives:</strong> In problem solving process, we have advanced the study of plithogenic interval valued neutrosophic hypersoft set, to analyse with all the ap…
View article: Research And Innovation In Biomedical Engineering
Research And Innovation In Biomedical Engineering Open
The Biomedical Engineering Department of Rajalakshmi Engineering College (REC) is hosting an International Conference, RIBE2023, on July 27-28, in a hybrid mode. The conference encompasses several tracks covering emerging and active areas …
View article: Image Clustering and Feature Extraction by Utilizing an Improvised Unsupervised Learning Approach
Image Clustering and Feature Extraction by Utilizing an Improvised Unsupervised Learning Approach Open
The need for information is gradually shifting from text to images due to the technology’s growth and increase in digital images. It is quite challenging for people to find similar color images. To obtain similarity matching, the color of …
View article: A Foreground Prototype-Based One-Shot Segmentation of Brain Tumors
A Foreground Prototype-Based One-Shot Segmentation of Brain Tumors Open
The potential for enhancing brain tumor segmentation with few-shot learning is enormous. While several deep learning networks (DNNs) show promising segmentation results, they all take a substantial amount of training data in order to yield…
View article: Exploring the Capabilities of a Lightweight CNN Model in Accurately Identifying Renal Abnormalities: Cysts, Stones, and Tumors, Using LIME and SHAP
Exploring the Capabilities of a Lightweight CNN Model in Accurately Identifying Renal Abnormalities: Cysts, Stones, and Tumors, Using LIME and SHAP Open
Kidney abnormality is one of the major concerns in modern society, and it affects millions of people around the world. To diagnose different abnormalities in human kidneys, a narrow-beam x-ray imaging procedure, computed tomography, is use…
View article: Automated Detection and Classification of Oral Squamous Cell Carcinoma Using Deep Neural Networks
Automated Detection and Classification of Oral Squamous Cell Carcinoma Using Deep Neural Networks Open
This work aims to classify normal and carcinogenic cells in the oral cavity using two different approaches with an eye towards achieving high accuracy. The first approach extracts local binary patterns and metrics derived from a histogram …
View article: Attention-effective multiple instance learning on weakly stem cell colony segmentation
Attention-effective multiple instance learning on weakly stem cell colony segmentation Open
The detection of induced pluripotent stem cell (iPSC) colonies often needs the precise extraction of the colony features. However, existing computerized systems relied on segmentation of contours by preprocessing for classifying the colony…
View article: Smart Diagnosis of Adenocarcinoma Using Convolution Neural Networks and Support Vector Machines
Smart Diagnosis of Adenocarcinoma Using Convolution Neural Networks and Support Vector Machines Open
Adenocarcinoma is a type of cancer that develops in the glands present on the lining of the organs in the human body. It is found that histopathological images, obtained as a result of biopsy, are the most definitive way of diagnosing canc…
View article: Zero-DCE++ Inspired Object Detection in Less Illuminated Environment Using Improved YOLOv5
Zero-DCE++ Inspired Object Detection in Less Illuminated Environment Using Improved YOLOv5 Open
Automated object detection has received the most attention over the years.Use cases ranging from autonomous driving applications to military surveillance systems, require robust detection of objects in different illumination conditions.Sta…
View article: Automated Bone Marrow Cell Classification for Haematological Disease Diagnosis Using Siamese Neural Network
Automated Bone Marrow Cell Classification for Haematological Disease Diagnosis Using Siamese Neural Network Open
The critical structure and nature of different bone marrow cells which form a base in the diagnosis of haematological ailments requires a high-grade classification which is a very prolonged approach and accounts for human error if performe…
View article: Deep Neural Network Models for Colon Cancer Screening
Deep Neural Network Models for Colon Cancer Screening Open
Early detection of colorectal cancer can significantly facilitate clinicians’ decision-making and reduce their workload. This can be achieved using automatic systems with endoscopic and histological images. Recently, the success of deep le…
View article: A FUZZY BASED DEEP LEARNING MODEL TO IDENTIFY THE PATTERN RECOGNITION FOR LICENSED PLATES IN SMART VEHICLE MANAGEMENT SYSTEM
A FUZZY BASED DEEP LEARNING MODEL TO IDENTIFY THE PATTERN RECOGNITION FOR LICENSED PLATES IN SMART VEHICLE MANAGEMENT SYSTEM Open
In general, vehicle management is based on the proper maintenance and safety of a vehicle. Based on this the quality of the vehicle is calculated. Most of the older vehicles are currently of poor quality and are producing high levels of po…