Dr.A.UMAMAGESWARI

@srmrmp.edu.in

Associate Professor
SRM Institute of Science and Technology, Ramapuram, Chennai

Dr.A.UMAMAGESWARI


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https://researchid.co/umamagea

EDUCATION

B.E.,M.

RESEARCH INTERESTS

Image Processing, Network Security, Machine Learning
43

Scopus Publications

396

Scholar Citations

8

Scholar h-index

8

Scholar i10-index

Scopus Publications

  • Automated speech-based assessment for mild cognitive impairment and Alzheimer's disease detection using progressive encoder–decoder feedback residual network with satin bowerbird optimization algorithm
    J A Jevin, A. Umamageswari
    Measurement Journal of the International Measurement Confederation, 2026
  • Transforming Education: The Role of AI Tools in Shaping Personalized and Inclusive Learning
    S. Deepa, Uma A. Mageswari
    Emerging Trends Global Perspectives and Systemic Transformation in AI, 2025
    This chapter investigates the profound influence of Artificial Intelligence (AI) on education, highlighting its role in transforming teaching strategies, student engagement, and personalized learning. It explores various AI-driven technologies, including machine learning, natural language processing (NLP), intelligent tutoring systems, and predictive analytics, which are reshaping the educational landscape. By enabling adaptive learning, personalized instruction, and improved accessibility, AI has the potential to make education more efficient and inclusive. However, the chapter also addresses key challenges, such as data privacy, algorithmic bias, and the digital divide, emphasizing the need for ethical and responsible AI implementation. Aimed at educators, policymakers, and researchers, this chapter provides a comprehensive analysis of AI's impact on modern education and the critical considerations for its integration.
  • Five-Tier BI Architecture with Tuned Decision Trees For E-Commerce Prediction
    Thiruneelakandan A, Umamageswari A
    International Journal of Basic and Applied Sciences, 2025
    In recent times, remarkable performance has been shown by Large Language Models (LLMs) in a range of Natural Language Processing (NLP) such as questioning, responding, document production, and translating languages. In today's competitive business landscape, understanding consumer behaviour in online buying is crucial for the success of e-commerce platforms. The work proposes a novel Five-Tier Service-Oriented BI Architecture (FSOBIA) that leverages Advanced Tuned Decision Tree (ATDT) techniques for predicting online buying behaviour. The proposed FSOBIA offers e-commerce platforms a scalable and adaptable solution for gaining insights into consumer preferences and making informed business decisions. The goal of FSOBIA's design and implementation is to meet the needs of evolving users and provide quicker service. Experimental evaluations on real-world datasets in FSOBIA achieved over 95% prediction accuracy, outperforming traditional models: Decision Trees (82%) and XGBoost (91%), while offering better scalability and computational efficiency.
  • Deep learning and image processing for cancer cell identification
    A. Umamageswari, S. Deepa, K. Raja
    AI in Diagnostic Radiology Clinical Applications and Case Based Insights, 2025
    One of the biggest causes of mortality globally is still cancer, and patient outcomes are greatly enhanced by early identification. Conventional cancer detection techniques, such manually analysing samples and medical pictures, are frequently laborious, arbitrary, and susceptible to human error. But the field of health diagnostics, especially cancer detection, has undergone a revolution with the introduction of deep learning, and image processing. The use of deep learning models, specifically Convolutional Neural Networks (CNNs), in combination with image processing methods to detect cancer cells in a variety of imaging modalities, including Computed Tomography (CT) scans, dermatoscopic, histopathology slides, and Magnetic Resonance Images (MRI) scans images, is thoroughly examined in this chapter.
  • A deep learning approach for recognizing ancient Tamil scripts from historical artifacts
    International Journal of Advanced Technology and Engineering Exploration, 2025
    Traditional methods of transcription and analysis of these scripts are time-consuming and rely on specialized epigraphists.In recent years, image processing and deep learning (DL) techniques have emerged as promising approaches to automate the recognition of ancient scripts.By combining optical character recognition (OCR) and convolutional neural networks (CNN), these advanced techniques enable computers to identify and interpret complex patterns in historical Tamil inscriptions, thereby facilitating the digital preservation of ancient knowledge [2,3].Tamil, one of the world's oldest
  • Analytics and Business Intelligence Tools in the Industry 4.0: A Survey
    Thiruneelakandan. A, Umamageswari. A
    International Conference on Emerging Technologies in Electronics and Green Energy Iceteg 2025, 2025
    The general meaning of the word Business is, an organization or an entity involved in commercial, industrial or professional activities of buying-selling-servicing processes. Intelligence is the higher-level activities - involving reasoning, mental representation, problem solving and decision making. The term Business Intelligence (BI) refers to the combination of the business strategies and trendy technologies - utilized together for the betterment of business outcomes. More-over, the term BI have become more predominant now-a-days as the other related technologies. The sophisticated techniques put forth by these technology domains towards BI, have taken it to the greater heights. And it compels us to define BI as a novel methodology comprising algorithmic and visualization packages that collects, stores, analyses and portrays the data in a more elegant way. From the analyzed data, the data analyst derives the hidden insights with which the business bureaucrats strategize their business plans in the market. And that helps business organization to leap forward and leverages the business. The world is full of numbers/data. But human brain could assimilate, interpret and remember the visuals better than raw data. Hence, it becomes important for the business organization to visualize their data metrics with suitable charts - which gauges the business executives to decide upon the business strategies. This work focuses upon the importance of representing the data in terms of visuals and it surveys various BI and Data Visualization (DV) tools used in the modern Industry era, Industry 4.0. Our key-findings includes: the emerging Analytics and Business Intelligence (ABI) tools are competing each other in offering AI-powered features and almost all the tools require the domain expert's involvement in the successful utilization of the ABI tools.
  • A Novel Approach for Automatic Prediction of Canine Impaction using Deep Learning Algorithms
    M. Faritha Begum, A. Umamageswari
    Proceedings of the 6th International Conference on Smart Electronics and Communication Icosec 2025, 2025
    Canine impaction is a common dental anomaly with significant implications for orthodontic treatment planning and patient outcomes. Early and accurate prediction of impacted canines is essential for minimizing complications such as root resorption, prolonged treatment duration, and surgical interventions. This paper proposes a novel deep learning-based framework for the automatic prediction of canine impaction using panoramic radiographs (orthopantomograms, OPGs). A convolutional neural network (CNN) architecture enhanced with transfer learning and attention mechanisms was developed to detect morphological and positional anomalies of the maxillary canines. The proposed model was trained on a curated dataset of annotated OPG images and evaluated against conventional diagnostic approaches and baseline machine learning methods. Experimental results demonstrate that the model achieves superior performance with accuracy of 95.4%, sensitivity of 94.2%, and specificity of 96.1%. Furthermore, the integration of Grad-CAM attention visualization provides interpretability, enabling clinicians to understand the model’s diagnostic focus. This study highlights the potential of deep learning algorithms in dental radiology for assisting orthodontists in early, precise, and automated canine impaction prediction.
  • Hybrid CNN-XGBoost Architecture for Predicting Chronic Kidney Disease from Clinical and Drug-Exposure Data
    R.Nithin Kumar, A. Umamageswari
    Proceedings of 8th International Conference on Computing Methodologies and Communication Iccmc 2025, 2025
    Deterioration of kidney function over time, culminating in renal failure and other serious complications, characterises CKD, a worldwide health problem. It is not uncommon for chronic kidney disease (CKD) to go undetected until it has advanced considerably because it does not manifest itself in its early stages. The key to reducing morbidity and death caused by a disease is early discovery and prompt action. In order to improve the data quality, this work suggests an AI-based method for predicting CKD employing sophisticated data pretreatment techniques, such as data transformation, encoding, and handling missing information. The preprocessed CKD datasets were subjected to five distinct feature extraction and evaluation methods. An improved model for prediction accuracy was created by merging CNNXG. This hybrid model is called CNNXGB. Outperforming previous prediction models, the suggested model achieved an RMSE of 0.03 and an MAE of 0.0021. Our results indicate that the CNNXGB model is a strong and trustworthy method for detecting CKD early on. This could lead to better patient management and less strain on healthcare systems.
  • Multi-biometric authentication system for enhancing the security levels in cloud computing using deep learning algorithm
    A. Umamageswari, S. Deepa, Sridevi S, A. Sangari
    Edelweiss Applied Science and Technology, 2025
    In recent years, cloud computing has surged in popularity, offering vast computational resources in a scalable, cost-efficient manner. Despite its benefits, security concerns persist, prompting many companies to adopt cloud computing despite the associated risks. To address challenges in password management and the efficacy of authentication systems, biometric authentication has garnered significant attention. As the imperative for personal data security intensifies, multi-biometric fusion-based identification systems emerge as a promising solution to bolster performance accuracy. This paper introduces a novel computational multimodal biometric recognition technique aimed at autonomously authenticating facial, iris, and fingerprint images using advanced deep learning methodologies. By integrating features using Fusion-Based Feature Extraction (Weighted Sum Rule), and classification using Deep Cross-Modal Retrieval (DCMR), this approach produces robust representations of facial, iris, and fingerprint characteristics by generating OTP (One-Time Password) to enhance authentication in the cloud environment. The efficacy of the proposed approach is evaluated by comparing its performance against established classifiers such as Support Vector Machines (SVM), Random Forests, Decision Trees, and K-Nearest Neighbors (KNN), utilizing metrics including recognition rate, precision, recall, and F-measure. Results demonstrate a recognition rate of 99.2%, surpassing alternative models considered. These findings highlight the potential of advanced deep learning methodologies within cloud computing environments to enhance multimodal biometric authentication systems. This approach utilizes Biometric-as-a-Service (BaaS) to streamline complexity and computational overhead, facilitating broader implementation of robust biometric security measures in cloud-based ecosystems.
  • Real-Time Multi-Modal Sign Language Recognition and Emotion Interpretation System
    Venkatesh S, Vamsi V, Jerome Reason, B Narayin Prashant, Santhosh Kumar C, A. Umamageswari
    2025 International Conference on Sensors and Related Networks Sennet 2025 Special Focus on Digital Healthcare 64220, 2025
    This study presents a real-time, multi-modal system that combines sign language gesture recognition with facial emotion analysis to improve accessibility in communication. Departing from conventional approaches that primarily address gesture interpretation, this system integrates emotional context to deliver more comprehensive and meaningful translations. Built using open-source tools such as TensorFlow, MediaPipe, OpenCV, and managed via Miniconda, the model achieves efficient performance while remaining lightweight and platform-agnostic. It leverages live webcam feeds, employing convolutional neural networks (CNNs) for gesture detection and facial landmark-based techniques for emotion classification. Designed with web compatibility in mind, the system can be deployed as a browser plugin or Chrome extension, enabling smooth integration into online environments. Experimental results demonstrate reliable accuracy and low processing latency, underscoring the system's viability for real-time applications. This work offers a scalable, user-friendly assistive technology aimed at reducing communication barriers for individuals who are deaf or hard of hearing.
  • Deep Belief Network-Based User and Entity Behavior Analytics (UEBA) for Web Applications
    S. Deepa, A. Umamageswari, S. Neelakandan, Hanumanthu Bhukya, I. V. Sai Lakshmi Haritha, Manjula Shanbhog
    International Journal of Cooperative Information Systems, 2024
  • Alzheimer's Disease Prediction using an Artificial Butterfly Optimizer with a Two-Layer CNN Approach
    J A Jevin, A. Umamageswari
    4th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2024, 2024
  • Generative AI: A Transformative Force in Business Intelligence
    Thiruneelakandan. A, Umamageswari. A
    2nd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2024, 2024
  • Machine Learning Model for Sentimental Analysis of Amazon Reviews
    A. Umamageswari, R.J. Pratishwaran, M. Poojitha Reddy, R. Yuvan Sankar Raj
    IEEE International Conference on Electronic Systems and Intelligent Computing Icesic 2024 Proceedings, 2024
  • Unleashing hidden canines: a novel fast R-CNN based technique for automatic auxiliary canine impaction
    International Journal of Advanced Technology and Engineering Exploration, 2024
  • Fast Moving Consumer Goods Object Detection Using YOLOV8
    A. Umamageswari, Mukund. P.U, Abhishek. V.B, Y. Devi Vaishnavi
    IEEE International Conference on Electronic Systems and Intelligent Computing Icesic 2024 Proceedings, 2024
  • EmotionFusion: A unified ensemble R-CNN approach for advanced facial emotion analysis
    A. Umamageswari, S. Deepa, A. Bhagyalakshmi, A. Sangari, K. Raja
    Journal of Intelligent and Fuzzy Systems, 2023
  • Vulnerability assessment in contemporary computing
    Umamageswari, S. Deepa
    Risk Detection and Cyber Security for the Success of Contemporary Computing, 2023
  • RETRACTION:A novel deep learning based underwater image de-noising and detecting suspicious object
    S. Padmapriya, A. Umamageswari, S. Deepa, J. Faritha Banu
    Journal of Intelligent and Fuzzy Systems, 2023
  • Web-based data manipulation to improve the accessibility of factory data using big data analytics: An industry 4.0 approach
    R. Vijayapriya, A. Umamageswari, Rohith Bhat, Ruby Dass, N. Manikandan
    Data Fabric Architectures Web Driven Applications, 2023
  • A Novel Fuzzy C-Means based Chameleon Swarm Algorithm for Segmentation and Progressive Neural Architecture Search for Plant Disease Classification
    A. Umamageswari, N. Bharathiraja, D. Shiny Irene
    ICT Express, 2023
  • Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases
    Deepa Sivapatham, Umamageswari Arasakumaran, Bhagyalakshmi Annappan, Shanmuganathan Chandrasekaran
    Traitement Du Signal, 2023
  • Cracks in Time: Analyzing Structural Deterioration in Ancient Monuments
    M. Snehapriya, A. Umamageswari
    3rd IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2023, 2023
  • Federated Learning Approach for Analyzing Electric Vehicle Sales in the Indian Automobile Market
    Thiruneelakandan. A, Umamageswari. A
    2023 IEEE International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2023, 2023
  • A Novel Hand Gesture Recognition for Aphonic People Using Convolutional Neural Network
    S. Deepa, A. Umamageswari, S. Menaka
    Lecture Notes in Electrical Engineering, 2023
  • Efficacy of V-Lab for Engineering Students during COVID-19
    J. Shiny Duela, A. Umamageswari, K. Raja, S. Suresh
    Redefining Virtual Teaching Learning Pedagogy, 2023
  • Quantum assisted Genetic Algorithm for Sequencing Compatible Amino Acids in Drug Design
    Shiny Duela J, Umamageswari A, Prabavathi R, Prashanth Umapathy, Raja K
    2023 3rd International Conference on Advances in Electrical Computing Communication and Sustainable Technologies Icaect 2023, 2023
  • An enhanced approach for leaf disease identification and classification using deep learning techniques
    A. Umamageswari, S. Deepa, K. Raja
    Measurement Sensors, 2022
  • An Enhanced Identification and Classification Algorithm for Plant Leaf Diseases Based on Deep Learning
    Umamageswari Arasakumaran, Shiny Duela Johnson, Dioline Sara, Raja Kothandaraman
    Traitement Du Signal, 2022
  • Achieving Linear and Systematic Perspectives to detect stroke rehabilitation exercise posture using Neural Network
    A. Umamageswari, S. Deepa, J.Faritha Banu
    Proceedings of the 3rd International Conference on Smart Technologies in Computing Electrical and Electronics Icstcee 2022, 2022
  • A Unified Methodology for Early recognition of Diabetic Retinopathy
    S. Deepa, A. Umamageswari, S. Shoba
    Proceedings of the 3rd International Conference on Smart Technologies in Computing Electrical and Electronics Icstcee 2022, 2022
  • Identifying Diabetics Retinopathy using Deep Learning based Classification
    A. Umamageswari, J. Shiny Duela, K. Raja
    2021 22nd International Arab Conference on Information Technology Acit 2021, 2021
  • Morphometry of the uncinate process, vertebral body, and lamina of the C3–7 vertebrae relevant to cervical spine surgery
    Veeramani Raveendranath, Thangarasu Kavitha, Amirthalingam Umamageswari
    Neurospine, 2019
  • Enhancing security in medical image informatics using geometrical attacks
    A. Umamageswari, M. A. Leo Vijilious
    Current Science, 2019
  • Enhancing Security in Medical Image Informatics with Various Attacks
    A. Umamageswari, A. Jebasheela, D. Ruby, M.A. Leo Vijilious
    2019 Innovations in Power and Advanced Computing Technologies I Pact 2019, 2019
  • Assessment of knowledge and practice toward disposal of expired drugs among medical professionals in chennai - A cross-sectional prospective study
    Umamageswari Arunachalam, Guru Scindia Mv, Priestly Vivekkumar S, Geetha R
    Asian Journal of Pharmaceutical and Clinical Research, 2017
  • Enhancing security in medical image communication using novel digital signature with various attacks
    Arpn Journal of Engineering and Applied Sciences, 2015
  • Novel algorithms for secure medical image communication using Digital Signature with various attacks
    A. Umamageswari, G.R. Suresh
    2013 5th International Conference on Advanced Computing Icoac 2013, 2014
  • Secure medical image communication using ROI based lossless watermarking and novel digital signature
    A. Umamageswari, G.R. Suresh
    Journal of Engineering Research, 2014
  • Secure medical image communication using ROI based lossless watermarking and novel digital signature
    A. Umamageswari, G.R. Suresh
    Journal of Engineering Research Kuwait, 2014
  • Novel algorithm for secure medical image communication using ROI based digital lossless watermarking and DS
    International Journal of Applied Engineering Research, 2014
  • Enhancing security in medical image communication with JPEG2000 compression and lossless watermarking
    A. Umamageswari, G. R. Suresh
    Lecture Notes in Electrical Engineering, 2013
  • Security in medical image communication with arnold's cat map method and reversible watermarking
    A. Umamageswari, G. R. Suresh
    Proceedings of IEEE International Conference on Circuit Power and Computing Technologies Iccpct 2013, 2013

RECENT SCHOLAR PUBLICATIONS

  • Deep Neural Network Powered System for Precision Breast Cancer Analysis and Stage Classification
    A Umamageswari, S Deepa, A Sangari
    INTERNATIONAL JOURNAL OF ADVANCES IN SIGNAL AND IMAGE SCIENCES, 1138-1150 , 2026
    2026
  • Deep Learning and Image Processing for Cancer Cell Identification
    A Umamageswari, S Deepa, K Raja
    AI in Diagnostic Radiology: Clinical Applications and Case-Based Insights, 1-40 , 2026
    2026
  • A Novel Approach for Automatic Prediction of Canine Impaction using Deep Learning Algorithms
    MF Begum, A Umamageswari
    2025 6th International Conference on Smart Electronics and Communication … , 2025
    2025
  • Automated speech-based assessment for mild cognitive impairment and Alzheimer’s disease detection using progressive encoder–decoder feedback residual network with satin …
    JJ Augustine, A Umamageswari
    Measurement, 118744 , 2025
    2025
  • Deep Learning Based Object Detection in Medical Image with YOLOv4-CSP with U-Net Algorithms.
    A Umamageswari, CS Anita, LS Beevi, A Sangari
    Traitement du Signal 42 (1) , 2025
    2025
  • Multi-biometric authentication system for enhancing the security levels in cloud computing using deep learning algorithm
    A Umamageswari, S Deepa, S Sridevi, A Sangari
    Edelweiss Applied Science and Technology 9 (5), 554-571 , 2025
    2025
    Citations: 1
  • Alzheimer's disease prediction using an artificial butterfly optimizer with a two-layer cnn approach
    JA Jevin, A Umamageswari
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024
    Citations: 2
  • Fast Moving Consumer Goods Object Detection Using YOLOV8
    A Umamageswari, M PU, A VB, YD Vaishnavi
    2024 International Conference on Electronic Systems and Intelligent … , 2024
    2024
    Citations: 2
  • Machine Learning Model for Sentimental Analysis of Amazon Reviews
    A Umamageswari, RJ Pratishwaran, MP Reddy, RYS Raj
    2024 International Conference on Electronic Systems and Intelligent … , 2024
    2024
  • Enhancing underwater object detection using advanced deep learning de-noising techniques
    A Umamageswari, S Deepa, FBJ Hussain, P Shanmugam
    Traitement du Signal 41 (5), 2593 , 2024
    2024
    Citations: 8
  • Deep belief network-based user and entity behavior analytics (ueba) for web applications
    S Deepa, A Umamageswari, S Neelakandan, H Bhukya, ...
    International Journal of Cooperative Information Systems 33 (02), 2350016 , 2024
    2024
    Citations: 4
  • Unleashing hidden canines: a novel fast R-CNN based technique for automatic auxiliary canine impaction
    S Deepa, A Umamageswari, L Sherinbeevi, A Sangari
    International Journal of Advanced Technology and Engineering Exploration 11 … , 2024
    2024
    Citations: 3
  • Cracks in Time: Analyzing Structural Deterioration in Ancient Monuments
    M Snehapriya, A Umamageswari
    2023 3rd International Conference on Mobile Networks and Wireless … , 2023
    2023
  • EmotionFusion: A unified ensemble R-CNN approach for advanced facial emotion analysis
    A Umamageswari, S Deepa, A Bhagyalakshmi, A Sangari, K Raja
    Journal of Intelligent & Fuzzy Systems 45 (6), 10141-10155 , 2023
    2023
    Citations: 2
  • Data Analytics: An Industry 4.0 Approach
    R Vijayapriya, A Umamageswari, R Bhat, R Dass
    Data Fabric Architectures: Web-Driven Applications, 19 , 2023
    2023
  • Efficacy of V‐Lab for Engineering Students during COVID‐19
    J Shiny Duela, A Umamageswari, K Raja, S Suresh
    Redefining Virtual Teaching Learning Pedagogy, 75-95 , 2023
    2023
  • A novel fuzzy C-means based chameleon swarm algorithm for segmentation and progressive neural architecture search for plant disease classification
    A Umamageswari, N Bharathiraja, DS Irene
    ICT Express 9 (2), 160-167 , 2023
    2023
    Citations: 116
  • Analysis of Genetic Face Images with Respect to Reflexology for Prediction of Diseases
    S Umamageswari, A., Deepa
    Traitement Du Signal 40 (1), 21-30 , 2023
    2023
    Citations: 1
  • Quantum assisted genetic algorithm for sequencing compatible amino acids in drug design
    S Duela, A Umamageswari, R Prabavathi, P Umapathy, K Raja
    2023 Third international conference on advances in electrical, computing … , 2023
    2023
    Citations: 12
  • 2 Web-Based Data Manipulation to Improve the Accessibility of Factory Data Using Big Data Analytics: An Industry 4.0 Approach
    R Vijayapriya, A Umamageswari, R Bhat, R Dass, N Manikandan
    De Gruyter , 2023
    2023
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • A novel fuzzy C-means based chameleon swarm algorithm for segmentation and progressive neural architecture search for plant disease classification
    A Umamageswari, N Bharathiraja, DS Irene
    ICT Express 9 (2), 160-167 , 2023
    2023
    Citations: 116
  • A survey on lossless compression for medical images
    MF Ukrit, A Umamageswari, GR Suresh
    International Journal of Computer Applications 31 (8), 47-50 , 2011
    2011
    Citations: 58
  • A survey on security in medical image communication
    A Umamageswari, MF Ukrit, GR Suresh
    International Journal of Computer Applications 30 (3), 41-45 , 2011
    2011
    Citations: 38
  • An enhanced approach for leaf disease identification and classification using deep learning techniques
    KR A. Umamageswari * , S. Deepa
    Measurement: Sensors 24 (100568), 8 , 2022
    2022
    Citations: 35
  • Security in medical image communication with arnold's cat map method and reversible watermarking
    A Umamageswari, GR Suresh
    2013 International Conference on Circuits, Power and Computing Technologies … , 2013
    2013
    Citations: 33
  • Quantum assisted genetic algorithm for sequencing compatible amino acids in drug design
    S Duela, A Umamageswari, R Prabavathi, P Umapathy, K Raja
    2023 Third international conference on advances in electrical, computing … , 2023
    2023
    Citations: 12
  • an enhanced identification and classification algorithm for plant leaf diseases based on deep learning
    KR A.Umamageswari, J.Shiny Duela, Diolin Sara
    Traitement Du Signal 39 (3), 1013-1018 , 2022
    2022
    Citations: 11
  • Secure medical image communication using ROI based lossless watermarking and novel digital signature
    AUGR Suresh
    Journal of engineering Research, Kuwait University 2 (3), 87-108 , 2014
    2014
    Citations: 11
  • Enhancing underwater object detection using advanced deep learning de-noising techniques
    A Umamageswari, S Deepa, FBJ Hussain, P Shanmugam
    Traitement du Signal 41 (5), 2593 , 2024
    2024
    Citations: 8
  • A novel hand gesture recognition for aphonic people using convolutional neural network
    S Deepa, A Umamageswari, S Menaka
    Computer Vision and Machine Intelligence Paradigms for SDGs: Select … , 2023
    2023
    Citations: 8
  • A Novel Approach for Classification of Diabetics from Retinal Image Using Deep Learning Technique
    LS Umamageswari, A., Deepa, S., & Beevi
    International Journal of health Sciences 6 (S1), 2729–2736 , 2022
    2022
    Citations: 8
  • A new cryptographic digital signature for secure medical image communication in telemedicine
    A Umamageswari, GR Suresh
    International Journal of Computer Applications 86 (11) , 2014
    2014
    Citations: 6
  • Identifying Diabetics Retinopathy using Deep Learning based Classification
    A Umamageswari, JS Duela, K Raja
    2021 22nd International Arab Conference on Information Technology (ACIT), 1-6 , 2021
    2021
    Citations: 5
  • Performance analysis of secure medical image communication with digital signature and reversible watermarking
    A Umamageswari, GR Suresh
    ictact journal on image and video processing 4 (01) , 2013
    2013
    Citations: 5
  • Enhancing security in medical image communication with JPEG2000 compression and lossless watermarking
    A Umamageswari, GR Suresh
    Proceedings of the Fourth International Conference on Signal and Image … , 2013
    2013
    Citations: 5
  • Deep belief network-based user and entity behavior analytics (ueba) for web applications
    S Deepa, A Umamageswari, S Neelakandan, H Bhukya, ...
    International Journal of Cooperative Information Systems 33 (02), 2350016 , 2024
    2024
    Citations: 4
  • Novel Algorithm for Secure Medical Image Communication Using ROI Based Digital Lossless Watermarking and DS
    AUDGR Suresh
    International Journal of Applied Engineering Research 9 (22), 12163-12176 , 2014
    2014
    Citations: 4
  • Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012): Volume 1
    S Mohan, SS Kumar
    Springer Science & Business Media , 2013
    2013
    Citations: 4
  • Security in medical image communication with ROI based lossless watermarking and digital signature
    A Umamageswari, GR Suresh
    the Proceedings of NCIEEE 13 , 2013
    2013
    Citations: 4
  • Unleashing hidden canines: a novel fast R-CNN based technique for automatic auxiliary canine impaction
    S Deepa, A Umamageswari, L Sherinbeevi, A Sangari
    International Journal of Advanced Technology and Engineering Exploration 11 … , 2024
    2024
    Citations: 3

Publications

Publications
International / National Journal


1. A.Umamageswari, S.Deepa, L.Sherin beevi(2022), “A Novel Approach for classification of diabetics from retinal image using deep learning technique”, International Journal Health Sciences, 6(S1), 2729-2736. Http:// (WoS Indexed)
2. A.Umamageswari, N.Bharathiraja, “Novel fuzzy c-means based chameleon swarm algorithm for segmentation and progressive neural architecture search for plant disease classification”, ICT Express – Elsevier, September 2021, , (SCI/WoS Indexed)
3. A.Umamageswari, , “Deep Learning based leaf disease identification using PNAS-progressive Neural Architecture Search”, Arabian Journal for Science and Engineering, Accepted and yet to publish for publication (SCI/WoS Indexed)
4. A.Umamageswari, M.A.Leo Vijilious, “Enhancing Security in Medical Image informatics with various Geometrical Attacks”, Current Science, August 2019, Vol, 2, No.3, . (SCI Indexed)
5. A.Umamageswari, Nancy.A, ., Radha RamMohan.S, Irrigation based on Web Weather Forecast”, Taga International journal, , ISSN:1748-0345(2018)(Annexure I)
6. A. Umamageswari, C.S. Somu, I. Arokia Mary and R. Balaji,”Integrated Secure Medical Image Transfer Framework”, International Journal of Printing, Packaging & Allied Sciences, Vol. 5, No. 1, February 2017 (Annexure I)
7. A.Umamageswari, M.A.Leo Vijilious,(2016), “A Novel Approach for cla