SRIVIDHYA E

@sathyabama.ac.in

Assistant Professor
Sathyabama Institute of Science and Technology

SRIVIDHYA E


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https://researchid.co/srividhyae

EDUCATION

B.Tech IT - 2006
ME CSE - 2014
PhD -2022

RESEARCH INTERESTS

Image Processing, Artificial Intelligence
26

Scopus Publications

201

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • PLANTSHIELD AI: An Integrated Deep Learning And Predictive Analytics Framework For Smart Pest Management And Data-Driven Rice Crop Disease Optimization
    P Pavithra, J Nithyasri, E. Srividhya, S Jayanthi
    Proceedings of the 2026 6th International Conference on Image Processing and Capsule Networks Icipcn 2026, 2026
    PlantShield AI represents a novel solution within the farming industry as it proposes an answer to a highly important issue plant pathology outbreaks and kills rice crops with pests and diseases through the combination of deep learning and predictive analytics. Accurately identifying and classifying rice diseases using crop images through Convolutional Neural Networks (CNNs) and predicting outbreaks of pests using time-series forecasting models using the historical and environmental data are the tasks of this system. It also helps to reduce the losses of yield and avoid unnecessary overuse of pesticides through early detection and accurate interventions. PlantShield AI is a developed system that was trained in MATLAB with the Image Processing Toolbox and Deep Learning Toolbox on a huge set of labeled healthy and diseased rice photos, which means high classification rates. The structure facilitates real time tracking and decision making which presents an effective scalable solution using data-driven technology that helps in achieving sustainability and growth of rice farming. This paper has shown that AI-based diagnostics and predictive analytics could be used to defend crops and manage resources better in the field of agriculture today.
  • AI-Powered Parkinson's Wellness Assistant Featuring Physiotherapy Guidance, Diet Management, and Cognitive Exercises
    Chandra Varshini R, Daahliya IH, Joshila Grace LK, L. Sujihelen, E. Srividhya, S. Jayanthi
    Ccic 2026 Contemporary Computing Innovations Conference 2026, 2026
  • Automated Number Plate Recognition System for Secure Zone Monitoring
    E. Srividhya, T. Chandra Siva Rama Raju
    Proceedings of the 7th International Conference on Intelligent Sustainable Systems Iciss 2025, 2025
    Automated Number Plate Recognition (ANPR) systems are now a major part of the modern security framework, and are of specific importance for monitoring and controlling access to secure areas. Through the integration of machine learning, optical character recognition (OCR), and real time data processing, this project proposes an advanced ANPR system with high accuracy and flexibility under non-controlled environment. It builds plate detection and character segmentation detection on the basis of deep learning models which are combined with robust preprocessing techniques to achieve robust performance under low visibility, blur and various plate formats. The increase in functionality of the system for secure access control depends on centralized database matching and real time alert generation. Beyond traditional accuracy and scalability, the proposed methodology delivers on important problems, including privacy compliance and environmental adaptability. The objective of this research is to reshape secure zone monitoring which provides a seamless, automated, and efficient vehicle identification and security management scheme.
  • Advances in Artificial Intelligence and Machine Learning in the Early Diagnosis of Parkinson's Disease: A Comprehensive Review
    M Yogapriya, E. Srividhya
    Proceedings of 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2025, 2025
    Parkinson ’s disease and other neurodegenerative diseases have a huge impact on the quality of life for a patient. It is difficult to detect this disease early, as the symptoms of the above disease are much like those of other neurological conditions. Early detection of Parkinson ’s disease is highly made possible by artificial intelligence and machine tools. This review discusses various artificial intelligence strategies such as convolutional neural network, support vector machine, and hybrid models. It describes challenges such as bias, feature extraction, and many other issues arising when using artificial intelligence. A number of datasets are utilized for the early diagnosis of the disease and development of its treatments. This review describes better way for future research and the generally available accuracy of early diagnosis of the disease.
  • A Soft Computing Approach for MANET Optimization via Hyper Sphere-PSO Framework
    Sorabh Sharma, E. Srividhya, Naveen N M, Beena Snehal Uphale, Gouri Shukla, K. Sriram Kumar
    2025 IEEE 5th International Conference on ICT in Business Industry and Government Ictbig 2025, 2025
    The given work suggests a method which is based on soft computing of optimizing MANETs through a Hyper Sphere-guided PSO. The model focuses on the problem of deployment of excessive sensor nodes and it intelligently clusters and energizes and activates them on a region basis; depending on region sensing requirements. Hypersphere approach can estimate sensor coverage by using a geometric model and directing optimal sensor deployment whereas PSO dynamically shapes node configurations to cover the maximum areas with minimum consumption of energy. This is the strategy that will enable the development of balanced sensing of MANETs but reduce unnecessary power consumption. The proposed model is dynamic and is to adapt to the different network demands and topologies, which increases the localization precision and the coverage use overlap. The simulation outcomes indicate that the Hyper SpherePSO strategy results in an increase in the packet delivery rate, improvement in delay, and battery life as compared to traditional ways of optimization. The adaptation of the soft computing techniques adds flexibility and effectiveness in the administering of the MANET scalability in uncertain and limited resource environment. This study can help prolong the sustainability of MANET where computational intelligence can be aligned to the green decision-making approaches. The proposed system has shown higher results in comparison with all other methods and could achieve maximum <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 5. 4 \%}$</tex> PFR and 84.2 % route stability in case of a static situation.
  • Automatic Plant Watering System based on the Environmental Changes
    16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
  • Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework
    Syed Thouheed Ahmed, T. R. Mahesh, E. Srividhya, V. Vinoth Kumar, Surbhi Bhatia Khan, Abdullah Albuali, Ahlam Almusharraf
    BMC Medical Imaging, 2024
    Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challenge. In this paper, we present a novel methodology for categorizing AIoMT devices through the application of decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying a system on standard IoT devices and labeled IoMT devices for training purposes and attribute extraction. Through this process, we extract and map the interconnected attributes from a global federated cum aggression server. The aim of this terminology is to extract interdependent devices via federated learning, ensuring data privacy and adherence to operational policies. Consequently, a global training dataset repository is coordinated to establish a centralized indexing and synchronization knowledge repository. The categorization process employs generic labels for devices transmitting medical data through regular communication channels. We evaluate our proposed methodology across a variety of IoT, IoMT, and AIoMT devices, demonstrating effective classification and labeling. Our technique yields a reliable categorization index for facilitating efficient access and optimization of medical devices within global servers.
  • The Evolution of Materials through Machine Learning for Enhanced Energy Storage Solutions
    E. Srividhya, Moumita Pal, Richa Agarwal, C. Sudha, V. R. Niveditha
    Introduction to Functional Nanomaterials, 2024
    This research explores the dynamic interface between material science and machine learning (ML) for advancing energy storage solutions. Evaluating state-of-the-art materials for batteries, the study addresses challenges in scalability, emphasising real-time applications of ML in material discovery. Adaptive ML techniques optimise energy storage systems, ensuring continuous refinement for enhanced cycle life. The integration of Materials Genome Initiative with ML propels accelerated materials discovery, unveiling quantum computing’s role and synergies with emerging technologies. The research delves into case studies, showcasing ML’s ongoing applications in battery material design and the learning derived from failures, guiding the evolution of predictive models. Ethical considerations and bias mitigation in ML-driven research are addressed in realtime. Future directions explore quantum computing’s current role in material science and synergies between ML and emerging technologies in energy storage research. Current insights encompass ML’s achievements in materials evolution, offering a roadmap for ML-driven energy storage solutions. Overall, this research contributes to a comprehensive understanding of the intricate interplay between material science and ML, charting a transformative path towards sustainable and innovative energy storage technologies.
  • Cloud based Threat Intelligence Sharing for Collective Defence
    M.S. Roobini, M. Bhargava Chowdary, Y. Srinivas, S. Jayanthi, E. Srividhya
    Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
    To improve cybersecurity, cloud-based threat intelligence sharing for collective defense is essential. Organizations must work together to effectively detect and respond to the variety of cyber dangers that exist in the linked world of today. The idea of using cloud infrastructure to share and analyze threat intelligence data in order to support collective defense is explored in this abstract. The cloud-based paradigm has many benefits, such as scalability, flexibility, and simplicity of access, which enables businesses to easily share useful intelligence and work together on threat mitigation tactics. Participating entities can improve their cyber defense capabilities by combining resources and knowledge through a common platform, taking use of the community's experience and collective knowledge. Moreover, the cloud-based architecture guarantees real-time data synchronization between enterprises, facilitating quick threat detection and response. In order to battle the growing cyber dangers that plague our digital environment, this abstract emphasizes the importance of cloud-based threat intelligence sharing for collective defense.
  • Designing an Ml-Powered Assistive Technology for People With Cognitive and Mental Disabilities
    M.S. Roobini, B. Bhavani Asish, Sujeeth Challa, G Kalaiarasi, E. Srividhya
    Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
    The development of an assistive device powered by machine learning (ML) for people with cognitive and mental disorders is highlighted in this abstract. The objective is to develop an intelligent system that will improve these people's independence, communication, and quality of life. This technology's design incorporates ML algorithms, sensorbased data collecting, and an intuitive user interface. The system can understand and adapt to the particular requirements and difficulties faced by people with cognitive and mental disorders by employing ML approaches. The machine learning algorithms are taught to comprehend and interpret user inputs including gestures, speech, and facial expressions and offer the proper help or interventions. The system may gather real-time data on the user's environment, activity, and emotional state thanks to the sensor-based data gathering, enabling personalized and context-aware support. People with different levels of cognitive ability can readily interact with the system thanks to the user-friendly interface. It features visual signals, natural language processing, and adjustable settings to suit personal tastes. The keywords for this abstract include: machine learning, assistive technology, cognitive disabilities, mental disabilities, independence, communication, quality of life, ML algorithms, sensor-based data collection, user-friendly interface, gestures, speech, facial expressions,personalized support, context-aware support, natural language processing, visual cues, and customizable settings.
  • Cloud-Enabled Isolation Forest for Anomaly Detection in UAV-Based Power Line Inspection
    Jayabharathi Ramasamy, E. Srividhya, V. Vaidehi, S. Vimaladevi, N. Mohankumar, S. Murugan
    Proceedings of the 2nd IEEE International Conference on Networking and Communications 2024 Icnwc 2024, 2024
  • Integrating lncRNA gene signature and risk score topredict recurrence cervical cancer using recurrent neural network
    E. Srividhya, V.R. Niveditha, C. Nalini, K. Sinduja, S. Geeitha, Kirubanantham P, Subrato Bharati
    Measurement Sensors, 2023
  • Small Single Board Computers based Smart Manhole Monitoring and Detection System
    N Vikram, Ramakrishnan Raman, J. Jagan Babu, E. Srividhya
    2023 4th International Conference on Electronics and Sustainable Communication Systems Icesc 2023 Proceedings, 2023
  • Cloud based Weather Station using IoT Technology to Track the Air Parameters
    S. Jayanthi, E. Srividhya, N. Ramshanka, Srinivasan T R, P. B. Edwin Prabhakar
    Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems Icears 2023, 2023
  • Sensor Node Communication based Selfish Node Detection in Mobile Wireless Sensor Networks
    S.John Justin Thangaraj, N. Ramshankar, E. Srividhya, S. Jayanthi, R. Kumudham, C. Srinivasan
    Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iciitcee 2023, 2023
  • Contact Tracing Detection Application for Covid-19 using Machine Learning Techniques
    M. Vengateshwaran, A. S Harshana, N. Valarmathi, S. Jayanthi, E. Srividhya
    Proceedings International Conference on Applied Artificial Intelligence and Computing Icaaic 2022, 2022
  • Diagnosis of Diabetes by Tongue Analysis
    E. Srividhya, A. Muthukumaravel
    Proceedings of 2019 International Conference on Computational Intelligence and Knowledge Economy Iccike 2019, 2019
  • Feature Extraction of Tongue Diseases Diagnosis Using SVM Classifier
    Srividhya E, Muthukumaravel A
    Proceedings of 2019 International Conference on Computational Intelligence and Knowledge Economy Iccike 2019, 2019
  • Diabetic detection using tongue images based on ANNclassification
    E. Srividhya, , Dr.A.Muthu Kumaravel, and
    International Journal of Engineering and Advanced Technology, 2019
  • Diagnosis of Diabetes by Tongue Analysis
    E. Srividhya, A. Muthukumaravel
    1st IEEE International Conference on Advances in Information Technology Icait 2019 Proceedings, 2019
  • Diabetes diagnostic method based on tongue image using ANN & CNN classifier
    International Journal of Recent Technology and Engineering, 2019
  • Prediction of diabetics using factor analysis
    International Journal of Recent Technology and Engineering, 2019
  • Diabetes diagnostic method based on tongue image using svm with gabor feature
    International Journal of Engineering and Advanced Technology, 2019
  • Optimized stack automated encoder for tongue diabetic classification
    Journal of Advanced Research in Dynamical and Control Systems, 2019
  • SVM and hough transform based tongue image analysis for medical diabetes diagnosis
    Journal of Advanced Research in Dynamical and Control Systems, 2017
  • Cloud based processing of multimedia in mobile application
    M. Ramasubramanian, M.A. Dorai Rangaswamy, E. Srividhya
    Proceedings Ncet Nres EM 2014 2nd IEEE National Conference on Emerging Trends in New and Renewable Energy Sources and Energy Management, 2015

RECENT SCHOLAR PUBLICATIONS

  • AI-Powered Parkinson's Wellness Assistant Featuring Physiotherapy Guidance, Diet Management, and Cognitive Exercises
    IH Daahliya, JG LK, L Sujihelen, E Srividhya, S Jayanthi
    2026 Contemporary Computing Innovations Conference (CCIC), 1-6 , 2026
    2026
  • PLANTSHIELD AI: An Integrated Deep Learning And Predictive Analytics Framework For Smart Pest Management And Data-Driven Rice Crop Disease Optimization
    P Pavithra, J Nithyasri, E Srividhya, S Jayanthi
    2026 6th International Conference on Image Processing and Capsule Networks … , 2026
    2026
  • A Soft Computing Approach for MANET Optimization via Hyper Sphere–PSO Framework
    KSK Sorabh Sharma, E Srividhya, Beena Snehal Uphale, Gouri Shukla
    2025 IEEE 5th International Conference on ICT in Business Industry … , 2025
    2025
  • Advances in Artificial Intelligence and Machine Learning in the Early Diagnosis of Parkinson’s Disease: A Comprehensive Review
    M Yogapriya, E Srividhya
    IEEE Xplore 1 (1), 1 , 2025
    2025
  • Automatic Plant Watering System based on the Environmental Changes
    ES Joshila Grace,Challapalli Naga Surya Sai Kiran,Selvi, Kalaiarasi,Jayanthi
    International Journal of Research in Engineering and Science (IJRES) 12 (12 … , 2025
    2025
  • Automated Number Plate Recognition System for Secure Zone Monitoring
    TCSRR Dr. E. Srividhya
    Proceedings of the 7th International Conference on Intelligent Sustainable … , 2025
    2025
    Citations: 2
  • The Evolution of Materials through Machine Learning for Enhanced Energy Storage Solutions
    E Srividhya, M Pal, R Agarwal, C Sudha, VR Niveditha
    Introduction to Functional Nanomaterials, 120-128 , 2024
    2024
  • Designing an Ml-Powered Assistive Technology for People With Cognitive and Mental Disabilities
    MS Roobini, BB Asish, S Challa, G Kalaiarasi, E Srividhya
    2024 Ninth International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 1
  • Cloud based threat intelligence sharing for collective defence
    MS Roobini, MB Chowdary, Y Srinivas, S Jayanthi, E Srividhya
    2024 Ninth International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 7
  • Cloud-enabled isolation forest for anomaly detection in UAV-based power line inspection
    J Ramasamy, E Srividhya, V Vaidehi, S Vimaladevi, N Mohankumar, ...
    2024 2nd International Conference on Networking and Communications (ICNWC), 1-6 , 2024
    2024
    Citations: 58
  • A REAL TIME HUMAN MOBILE ROBOT INTERACTION SYSTEM BASED ON HAND GESTURE USING RASPERRY pi
    J PATHANGE PAVAN, VISHWAJEET ANAND,DR.S.JAYANTHI,DR.E.SRIVIDHYA
    IN Patent 202,441,020,896 , 2024
    2024
  • Auto Correct of the Word in a Sentence Using Test Feature Analysis with Natural Language Process
    DLVKR Dr.E.Srividhya, Chunduri Sai Ganesh
    International Journal of Multidisciplinary Research(IJMR) 6 (2), 1-4 , 2024
    2024
  • A Cutting-Edge Framework for Efficient Image Dehazing and Accurate Image Segmentation Using Advanced Deep Learning Techniques
    SE Mithinesh Jaya Kumar Sankarapu, Shanmugaraj D, Kalairasi G, Selvi M ...
    Directory of Open Access Journals -Springer 112, 866-875 , 2024
    2024
    Citations: 1
  • Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework
    A Srividhya E Ahmed, S.T. , Mahesh, T.R. , Albuali, A. , Almusharraf
    BMC Medical Imaging 24 (1), 105 , 2024
    2024
    Citations: 30
  • SOLAR BASED AUTOMATED RAILWAY TRACK INSPECTION TROLLEY
    MARAJA Mr.VENGATESHWARAN MASILAMANI, Dr.JAYANTHI SAMPATH, Dr.SRIVIDHYA ...
    US Patent 6,319,705 , 2023
    2023
    Citations: 5
  • Small Single Board Computers based Smart Manhole Monitoring and Detection System
    N Vikram, R Raman, JJ Babu, E Srividhya
    2023 4th International Conference on Electronics and Sustainable … , 2023
    2023
    Citations: 2
  • Integrating lncRNA gene signature and risk score topredict recurrence cervical cancer using recurrent neural network
    E Srividhya, VR Niveditha, C Nalini, K Sinduja, S Geeitha, S Bharati
    Measurement: Sensors 27, 100782 , 2023
    2023
    Citations: 5
  • Cloud based Weather Station using IoT Technology to Track the Air Parameters
    S Jayanthi, E Srividhya, N Ramshankar, S TR, PBE Prabhakar
    2023 Second International Conference on Electronics and Renewable Systems … , 2023
    2023
    Citations: 4
  • Sensor Node Communication based Selfish Node Detection in Mobile Wireless Sensor Networks
    SJJ Thangaraj, N Ramshankar, E Srividhya, S Jayanthi, R Kumudham, ...
    2023 International Conference on Intelligent and Innovative Technologies in … , 2023
    2023
    Citations: 50
  • An Approach to Deep Learning
    MAS Dr.E.Srividhya Dr.S.Jayanthi Mrs.C.M.Suja, Mrs.Niveditha
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Cloud-enabled isolation forest for anomaly detection in UAV-based power line inspection
    J Ramasamy, E Srividhya, V Vaidehi, S Vimaladevi, N Mohankumar, ...
    2024 2nd International Conference on Networking and Communications (ICNWC), 1-6 , 2024
    2024
    Citations: 58
  • Sensor Node Communication based Selfish Node Detection in Mobile Wireless Sensor Networks
    SJJ Thangaraj, N Ramshankar, E Srividhya, S Jayanthi, R Kumudham, ...
    2023 International Conference on Intelligent and Innovative Technologies in … , 2023
    2023
    Citations: 50
  • Towards blockchain based federated learning in categorizing healthcare monitoring devices on artificial intelligence of medical things investigative framework
    A Srividhya E Ahmed, S.T. , Mahesh, T.R. , Albuali, A. , Almusharraf
    BMC Medical Imaging 24 (1), 105 , 2024
    2024
    Citations: 30
  • Diagnosis of Diabetes by Tongue Analysis
    DAM E.Srividhya
    IEEE International Conference on Computational Intelligence and Knowledge … , 2019
    2019
    Citations: 16
  • Cloud based threat intelligence sharing for collective defence
    MS Roobini, MB Chowdary, Y Srinivas, S Jayanthi, E Srividhya
    2024 Ninth International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 7
  • Feature Extraction of Tongue Diseases Diagnosis using SVM Classifier
    DAM E.Srividhya
    IEEE International Conference on Computational Intelligence and Knowledge … , 2019
    2019
    Citations: 6
  • Location based orphanage finder application for Google android phones
    SA D. Saranya S.Muthuselvan, E. Srividhya, S.R. Miruthula
    International Journal of Pure and Applied Mathematics 119 (16), 2009-2015 , 2018
    2018
    Citations: 6
  • SOLAR BASED AUTOMATED RAILWAY TRACK INSPECTION TROLLEY
    MARAJA Mr.VENGATESHWARAN MASILAMANI, Dr.JAYANTHI SAMPATH, Dr.SRIVIDHYA ...
    US Patent 6,319,705 , 2023
    2023
    Citations: 5
  • Integrating lncRNA gene signature and risk score topredict recurrence cervical cancer using recurrent neural network
    E Srividhya, VR Niveditha, C Nalini, K Sinduja, S Geeitha, S Bharati
    Measurement: Sensors 27, 100782 , 2023
    2023
    Citations: 5
  • Cloud based Weather Station using IoT Technology to Track the Air Parameters
    S Jayanthi, E Srividhya, N Ramshankar, S TR, PBE Prabhakar
    2023 Second International Conference on Electronics and Renewable Systems … , 2023
    2023
    Citations: 4
  • Contact Tracing Detection Application for Covid-19 using Machine Learning Techniques
    Srividhya, E , Vengateshwaran, M. , Harshana, A.S. , Valarmathi, N ...
    International Conference on Applied Artificial Intelligence and Computing … , 2022
    2022
    Citations: 3
  • Automated Number Plate Recognition System for Secure Zone Monitoring
    TCSRR Dr. E. Srividhya
    Proceedings of the 7th International Conference on Intelligent Sustainable … , 2025
    2025
    Citations: 2
  • Small Single Board Computers based Smart Manhole Monitoring and Detection System
    N Vikram, R Raman, JJ Babu, E Srividhya
    2023 4th International Conference on Electronics and Sustainable … , 2023
    2023
    Citations: 2
  • Diabetic Detection Using Tongue Images based on ANN Classification
    DAM E.Srividhya
    International Journal of Engineering and Advanced Technology 9 (1) , 2019
    2019
    Citations: 2
  • Cloud based processing of multimedia in mobile application
    E Srividhya
    2014 IEEE National Conference on Emerging Trends In New & Renewable Energy … , 2014
    2014
    Citations: 2
  • Designing an Ml-Powered Assistive Technology for People With Cognitive and Mental Disabilities
    MS Roobini, BB Asish, S Challa, G Kalaiarasi, E Srividhya
    2024 Ninth International Conference on Science Technology Engineering and … , 2024
    2024
    Citations: 1
  • A Cutting-Edge Framework for Efficient Image Dehazing and Accurate Image Segmentation Using Advanced Deep Learning Techniques
    SE Mithinesh Jaya Kumar Sankarapu, Shanmugaraj D, Kalairasi G, Selvi M ...
    Directory of Open Access Journals -Springer 112, 866-875 , 2024
    2024
    Citations: 1
  • Tongue Image Analysis for Medical Diabetes Diagnosis Using Canny Edge Algorithm
    DAM E.Srividhya
    Journal of Computational and Theoretical Nanoscience , 2020
    2020
    Citations: 1
  • AI-Powered Parkinson's Wellness Assistant Featuring Physiotherapy Guidance, Diet Management, and Cognitive Exercises
    IH Daahliya, JG LK, L Sujihelen, E Srividhya, S Jayanthi
    2026 Contemporary Computing Innovations Conference (CCIC), 1-6 , 2026
    2026
  • PLANTSHIELD AI: An Integrated Deep Learning And Predictive Analytics Framework For Smart Pest Management And Data-Driven Rice Crop Disease Optimization
    P Pavithra, J Nithyasri, E Srividhya, S Jayanthi
    2026 6th International Conference on Image Processing and Capsule Networks … , 2026
    2026