TERESA

@sece.ac.in

Associate Professor, Electronics and Communication Engineering
Sri Eshwar College of Engineering

TERESA


               Download Compact PDF  
https://researchid.co/vvteresa

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Electrical and Electronic Engineering
23

Scopus Publications

91

Scholar Citations

6

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • A blockchain-driven intrusion detection model for secure communication in IoT-WSN mesh architectures
    G. Elumalai, J. Arun Kumar, P. Sivakumar, V. V. Teresa
    Peer to Peer Networking and Applications, 2026
    The IoT-WSNs face the challenge of intrusion detection in wireless sensor networks due to dynamic patterns of traffic, limited resources of nodes, threat to privacy and susceptibility to routing and learning level attacks. Current intrusion detection systems (IDS) are either centralized learning which compromises on privacy and scalability or use federated learning which is not robust enough to handle model poisoning, manipulation of trust and routing level attacks. Furthermore, blockchain-based IDS systems have significant latency and overhead that restrict their functionality in resource-limited WSN. These constraints indicate a critical breach when it comes to realizing the lightweight, privacy-preserving, and trust-aware intrusion detection with a realistic implementation cost. This paper will fill this gap by proposing a secure federated blockchain-enabled IDS model of IoT-WSNs called SecuMesh-Net. The framework combines a temporal anomaly detector, based on Autoencoder and GRU, with federated learning to train models when decentralized, data privacy through the use of differential privacy, and finally, a blockchain based on PBFT to allow trust auditing and enforce routing security. The smart contracts provide trust- and energy-aware routing by isolating malicious nodes in real time and maintain the stability of the network. SecuMesh-Net is novel in its integrated approach to the time anomaly modelling, federated learning resilience, and lightweight blockchain auditing, separating consensus and operations of the IDS that require low latency. Comprehensive experiments based on real intrusion traces and traffic generated on NS-3 show that SecuMesh-Net has 97.4% detection, 2.1% false positive and 61 ms average latency, and per-event energy use of 2.4 mJ. These findings affirm the applicability, effectiveness, and suitability of the framework to practical uses of the IoT-WSN.
  • Thermal vision for lady finger quality assessment: A three-stage convolutional neural network approach
    Santi Kumari Behera, P Bharat Siva Varma, V V Teresa, Kalyan Das, Prabira Kumar Sethy, Aziz Nanthaamornphong
    International Journal of Food Science and Technology, 2025
    Lady finger is an important commercial crop that is nutritionally rich and has extensive culinary applications. The present research paper introduced a new technique for the nondestructive postharvest classification of okra pods (Clemson Spineless type) into suitably matured or overmatured okra pods using thermal images and the three-stage convolutional neural network (CNN) technique based on EfficientNetB7. For the thermal photography of lady finger pods, an FLIR E75 Thermal imaging unit was used, and the distance of both the cameras and lady finger was kept at a minimum of more than 0.5 m. The proposed CNN-based technique results were reported in the form of accuracy, sensitivity, specificity, precision, and F1-score, which were 0.9700, 0.9800, 0.9600, 0.9608, and 0.9703, respectively. In other words, the FPR for our classification model was reported to be 0.0400. The results of MCC and kappa statistics were also reported to be 0.9402 and 0.9400, which indicates that a strong agreement was found between the predicted and actual classifications of overmature and suitably matured okra pods. The experiment shows that the suggested approach could be utilised for the nondestructive classification of lady finger pods into suitably matured or overmatured ones.
  • AREA-DELAY-POWER-EFFICIENT GDI ARCHITECTURE SELECT ADDER TO CARRY
    R. Saranya, B. Paulchamy, K. Kalpana, V.V. Teresa, P. Logamurthy
    E3s Web of Conferences, 2025
    The signal processing system is extremely popular in this day and age. All of the primary circuits in the digital signal processing system are built around the adder, which is the fundamental building block. Today’s needs for lowering the delay, space, and power consumption of adder circuits boost the overall efficiency of the system, propelling it to the next stage of technological development. Despite the fact that the Carry Select Adder (CSLA) takes up more space, it is being utilised in place of the ripple carry adder in order to reduce propagation delays. In other models, a Carry Select Adder based on a Binary to Excess-I Converter (BEC) was utilised, which required fewer logic resources than a standard CSLA and was hence more energy efficient. The fact that these CSLAs reject one sum after the calculation, however, means that they are not more efficient. As a result, the delay was not significantly decreased. It is necessary to apply the reduced logic CSLA in order to overcome this challenge. However, by employing the Gate Diffusion Input (GDI) Technique, it is possible to achieve a lower delay than the previously suggested reduced logic CSLA. The suggested technique consumes less power and has a shorter propagation latency than existing techniques. In addition, the number of transistors necessary for the circuit was reduced by implementing this GDI-based CSLA. It is possible to create an efficient adder using this technique, as seen above.
  • A Compact Proximity-Coupled Antenna Array for Multi-Band 5G and 6G Wireless Communication Systems
    Sreejith. A.R, K.K. Anilkumar, Bose. V.V, V.V. Teresa
    Proceedings 2025 2nd International Conference on Electronic Circuits and Signaling Technologies Icecst 2025, 2025
    The rapid evolution of wireless communication technologies demands compact, high-performance antenna systems that can support multi-band operation across both sub-6 GHz and millimeter-wave (mmWave) spectra. In this work, we present a compact proximity-coupled antenna array designed specifically for multi-band 5G and 6G wireless communication systems. The proposed design employs a dual-layer substrate structure with proximity coupling between the feedline and radiating patch, enabling enhanced impedance bandwidth and radiation efficiency while maintaining a low-profile configuration. The antenna is optimized to operate at 3.5 GHz (n78), <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$28 \text{GHz}(5 \mathrm{G} \text{mmWave})$</tex>, and 140 GHz (targeted 6G band), achieving a measured impedance bandwidth of 13.2%, 18.5%, and 11.6% respectively at each band. The antenna gain reaches up to 8.7 dBi at 28 GHz and 10.4 dBi at 140 GHz, making it highly suitable for high-data-rate and long-range communication. The array configuration exhibits excellent port isolation (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt;30\ \text{dB}$</tex>) and a low envelope correlation coefficient (ECC <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;0.005$</tex>), ensuring its viability for MIMO applications. Moreover, the overall antenna footprint is compact (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$15 \text{mm} \times 12$</tex> mm per element), facilitating integration into mobile and IoT platforms. The proposed antenna demonstrates stable radiation patterns, with cross-polarization levels below −20 dB, and maintains over 85% radiation efficiency across all targeted bands. These results validate the potential of proximity-coupled techniques in enabling compact, wideband, and high-gain antenna arrays for next-generation wireless systems, particularly for 5G/6G dual-mode devices and intelligent communication environments.
  • EdgeMeshNet: RSSI- Based Vehicular Mesh Network for Accident Alerts in Mountainous Regions
    Vigneshkumar R, Sudheshna P, Sudharshana D, Sreenithi V, Teresa V V
    IC Decon 2025 2025 International Conference on Data Energy and Communication Network Proceedings, 2025
    A top way to reduce fatalities and injuries is providing accident event reporting in a timely manner. This can often be an issue in rural and mountainous area where the cell phone signal is limited, low or non-existent. This can cause delays in emergency support and assistance for a reporting party if systems of communication fail. The rugged terrain can limit or blind radio signals, and the available cell towers may not provide coverage, and texting a report may not be viable. Also be aware that the decision process of an accident report for some individuals is influenced by their fear of repercussions. Cellular communication between cars is not solacious much of use and often just utilizing basic communication such as verbal or text message. To alleviate some of these areas of concern, this study calls to introduces EdgeMeshNet, an intelligent car communication system that allow vehicles to communicate directly to the road signs and other vehicles via a mesh network. The EdgeMeshNet mesh network is established ad hoc, and it establishes a self-healing type of connectivity if faulty connections exist. Specific to EdgeMeshNet, it will not use cellular networks to establish connectivity. The vehicular communication scheme will use a peer-to-peer type arrangement wherein vehicles can communicate and receive information from their own sensors (vehicles) as well their peers (other vehicles). The Edge nodes use the signal strength parameters to find the ideal path for message travelling “routes”, so that even in continuous change and constant travel situation there are advantages to communicating. EdgeMeshNet is developed with the ESP8266 low-power wireless modules and simulated on the Arduino IDE. It consists of three main features: (1) fast accident alerts, (2) high message delivery rate regardless of few cars or many cars on the road, and (3) the system works well with very little energy. The revised design does not need drastic changes to the roadways, making it affordable and practical. EdgeMeshNet provides real-time accident notifications where there is little or no cell coverage to facilitate quicker and better coordinated emergency responders, which will save lives on high-speed mountain roads with frequent automobile accidents.
  • A hybrid approach for soil classification: integrating lightweight convolutional neural network, attention mechanisms, and color features under resource constraints
    Santi Kumari Behera, Sachin Vishwakarma, V. V. Teresa, Ashoka Kumar Ratha, Prabira Kumar Sethy, Aziz Nanthaamornphong
    Proceedings of the Indian National Science Academy, 2025
  • An Integrated IoT Architecture for Real-Time Detection and Remote Tracking of Dementia Symptoms
    D. Shamia, V.V. Teresa, Harish Ragavendra M, Kaviarasu P, Akash R, Simiyon A
    Proceedings of International Conference on Modern Sustainable Systems Cmss 2025, 2025
    Dementia is a degenerative neurological condition that significantly affects both mental and physical abilities. Detecting the condition early and continuously tracking its progression are vital for improving patient outcomes and reducing the strain on caregivers. This paper introduces an IoT-enabled monitoring solution specifically designed for individuals with dementia. The proposed system combines wearable biomedical sensors, real-time data acquisition, and cloud-based analytics to monitor key physiological and cognitive indicators. At its core, the system utilizes an ESP32 microcontroller to collect real-time information from sensors such as ECG, heart rate, pulse oximeter, and body temperature sensors enabling the identification of dementia-related symptoms. When irregularities are identified, the system activates a buzzer and sends immediate alerts via the cloud to caregivers, medical professionals, and family members. The cloud platform facilitates not only remote observation but also pattern detection and long-term data trend analysis. In contrast to conventional methods, this approach offers better accuracy, lower costs, and improved accessibility, while also addressing issues like inconsistent data and low patient compliance. Experimental testing confirms the system’s effectiveness in identifying abnormal physiological states, suggesting its potential in early diagnosis and long-term dementia care. Future enhancements will focus on incorporating machine learning for predictive analysis and developing strategies to improve user interaction and adoption.
  • Integrating Sentiment Analysis with Learning Analytics for Improved Student
    B. Paulchamy, Vairaprakash Selvaraj, N.M. Indumathi, K. Ananthi, V.V. Teresa
    International Journal of Computational and Experimental Science and Engineering, 2024
    The integration of sentiment analysis with learning analytics offers a novel approach to improving student outcomes by providing deeper insights into the emotional and cognitive states of learners. This research explores the use of sentiment analysis on student interactions, such as online discussions, assignments, and feedback, to assess the emotional tone of student engagement. By combining these sentiment insights with traditional learning analytics, which track academic progress and behavior patterns, this study aims to create a comprehensive model that enhances the identification of students at risk, tailor educational interventions, and fosters personalized learning experiences. The proposed approach not only improves the monitoring of student well-being and engagement but also supports the development of adaptive learning systems that respond to students’ emotional states. Results show that sentiment analysis integrated with learning analytics can provide real-time feedback for educators, enhancing student support and improving overall academic performance
  • An Energy-Efficient improved Grey Wolf Optimization Algorithm-Based Cluster Head and Shamir Secrets Sharing-Based WSNs with Secure Data Transfer
    Yuvaraja M, Sureshkumar S, Joseph James S, Teresa V V
    Salud Ciencia Y Tecnologia Serie De Conferencias, 2024
    Introduction: Due to its self-configurability, ease of maintenance, and scalability capabilities, WSNs (Wireless Sensor Networks) have intrigued plenty of interest in a variety of fields. To move data within the network, WSNs are set up with more nodes. The security of SNs (sensing nodes), which are vulnerable to malevolent attackers since they are network nodes, is a crucial element of an IoT (Internet of Things)-based WSN. This study's primary objective is to provide safe routing and mutual authentication with IoT-based WSNs. Methods: The basic GWO algorithm's imbalances between explorations and mining, lack of population heterogeneity, and early convergences are all issues that this paper addresses by selecting energy-efficient CHs (cluster Heads) using EECIGWO algorithm, an upgraded version of the GWO, is used. Mean distances within clusters, well-spaced residual energies, and equilibrium of CHs are all factors that influence the choices of CHs. The average intra-cluster distances, sink distances, residual energies, and CHs balances are some of the criteria used to choose CHs. Results and Discussion: The proposed EECHIGWO-based clustering protocol's average throughput, dead node counts, energy consumption, and operation round counts have all been evaluated. Additionally, mutual authentication between the nodes is provided through SSS (Shamir Secret Sharing) mechanism. PDR (Packet Delivery Ratio) analysis is used to assess how well the EECHIGWO-IOT-WSNs are performing. Conclusion: The suggested proposed approach is assessed against existing methods like HHH-SS (Hybrid Harris Hawk and Salp Swarm), ESR (Energy-efficient and Secure Routing) protocol, and LWTS (Light Weight Trust Sensing) approaches in terms of AEED (Average End-to-End Delay), network overheads, and PLR (Packet Loss Ratio).
  • Efficient Nano-Scale Design of TIEO Based Reversible Logic Toffoli Gate Priority Encoder in Quantum-Dot Cellular Automata
    K. Kalpana, K. Sivakami, N. Revathi, S.M. Deepa, V.V. Teresa
    E3s Web of Conferences, 2024
    The goal of this research is to create a QCA-based reversible priority encoder. It is one of the most crucial parts of the encoding and decoding process. This novel nanotechnology, known as quantum-dot cellular automata (QCA), shows promise as a foundation for the development of reversible circuits. This paper proposes a simple, reversible, 4-2 line priority encoder design for the QCA platform. Using the simple and cheap Toffoli gate architecture, a reversible encoder circuit may be built. To analyze the proposed designs’ structural soundness, the simulation program QCA Designer is used.
  • Reversible Logic Toffoli Gate Priority Encoder for Effective Nano-Scale Application in QCA Paradigm
    K. Kalpana, B. Paulchamy, V. V. Teresa, K. Sivakami, S. M. Deepa, N. Revathi
    Communications in Computer and Information Science, 2024
  • Auto Sorting and Placing of Objects using Robotics Vision Module in MELFA Industrial Robot
    Kirti Mahajan, Pallavi Mane, Syed Mohammed Arif, Kamalakar Ravindra Desai, Girish Madhaorao Lonare, V. V. Teresa
    Proceedings 2024 5th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2024, 2024
  • AI-Enhanced Security Architecture for 6G Networks: A Federated Learning and Multi-Agent Approach
    V.V Teresa, J. Dhanaseker, S Arjun, R Naveenraj, A Antru Subil, Pm Ahmed Najeeb
    International Conference on Computing and Intelligent Reality Technologies Proceedings of Iccirt 2024, 2024
  • Improving Vehicle Security using CNN and Internet of Things Based Face Identification
    S. Nandhini, T. Bhuvaneswari, V. Bhuvaneshwari, V. V. Teresa, S. Anitha, K. Sivaprakash
    2024 International Conference on Cognitive Robotics and Intelligent Systems Icc Robins 2024, 2024
  • Performance analysis of alternating minimization based low complexity detection for MIMO communication system
    Kasiselvanathan M., Manikandan Rajagopal, Teresa V. V., Prabhakar Krishnan
    Automatika, 2023
  • Analysis of ECG Noise Cancellation and Abnormality Classification using Various Adaptive Algorithms
    S M Ramesh, S Nithya, V. V. Teresa, V Uma Maheswari, M A Raja, S Krishnakumar
    International Conference on Applied Intelligence and Sustainable Computing Icaisc 2023, 2023
  • LoRa Enhanced Real-Time Earthquake Monitoring System for Constructions Using IoT and Cloud
    V.V. Teresa, T. Thamaraimanalan, S. Jeevanantham, A. Balaji, H. Gokulanand, N. Jeevanprasath
    7th International Conference on Electronics Communication and Aerospace Technology Iceca 2023 Proceedings, 2023
  • Intelligent System for Monitoring Line of Safety in Railway Platforms
    M. Kasiselvanathan, V.V. Teresa, K. Sangeetha, Arunraja A
    4th International Conference on Inventive Research in Computing Applications Icirca 2022 Proceedings, 2022
  • Design of High Isolation MIMO Antennas for Ultra-Wide Band Communication
    T. Sathiyapriya, V. Gurunathan, J. Dhanasekar, V. V. Teresa
    Lecture Notes in Electrical Engineering, 2022
  • IoT-based Underground Cable Fault Detection
    V.V. Teresa, K. Rajeshwaran, S.Satheesh Kumar, S. Vishnupriyan, S. Dhanasekaran
    Proceedings International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2022, 2022
  • Design and Development of movable antenna system for multiplatform wireless communication
    S. Nithya, T. Jagadesh, E. Shalini, T. Sathiyapriya, V. V Teresa, P R. Buvaneswari
    Mysurucon 2022 2022 IEEE 2nd Mysore Sub Section International Conference, 2022
  • Improved modified area efficient carry select adder (MAE-CSLA) without multiplexer
    B Anand, V. V Teresa
    Journal of Computational and Theoretical Nanoscience, 2017
  • An improved low power and modified area efficient carry select adder – (MA-CSLA)
    International Journal of Applied Engineering Research, 2015

RECENT SCHOLAR PUBLICATIONS

  • A blockchain-driven intrusion detection model for secure communication in IoT-WSN mesh architectures
    G Elumalai, JA Kumar, P Sivakumar, VV Teresa
    Peer-to-Peer Networking and Applications 19 (2), 60 , 2026
    2026
  • Cross-Technology Evaluation of a Gate-Diffusion-Input Magnitude Comparator for Scalable CMOS Architectures
    VV Teresa, AN Duraivel, MS Kokilamani
    INTERNATIONAL JOURNAL OF ADVANCES IN SIGNAL AND IMAGE SCIENCES, 104-123 , 2026
    2026
  • A hybrid approach for soil classification: integrating lightweight convolutional neural network, attention mechanisms, and color features under resource constraints
    SK Behera, S Vishwakarma, VV Teresa, AK Ratha, PK Sethy, ...
    Proceedings of the Indian National Science Academy, 1-10 , 2025
    2025
    Citations: 1
  • A Compact Proximity-Coupled Antenna Array for Multi-Band 5G and 6G Wireless Communication Systems
    S AR, KK Anilkumar, B VV, VV Teresa
    2025 2nd International Conference on Electronic Circuits and Signaling … , 2025
    2025
  • A Novel RNN-based Framework for Accurate Detection and Prediction of Heart Disease
    K Kalpana, VV Teresa, VS MM
    2025 3rd International Conference on Sustainable Computing and Smart Systems … , 2025
    2025
  • An Integrated IoT Architecture for Real-Time Detection and Remote Tracking of Dementia Symptoms
    D Shamia, VV Teresa
    2025 International Conference on Modern Sustainable Systems (CMSS), 854-859 , 2025
    2025
  • Thermal vision for lady finger quality assessment: a three-stage convolutional neural network approach
    SK Behera, PBS Varma, VV Teresa, K Das, PK Sethy, ...
    International Journal of Food Science and Technology 60 (2), vvaf171 , 2025
    2025
    Citations: 1
  • Area-Delay-Power-Efficient GDI Architecture Select Adder to Carry
    R Saranya, B Paulchamy, K Kalpana, VV Teresa, P Logamurthy
    E3S Web of Conferences 616, 02005 , 2025
    2025
  • Ai-enhanced security architecture for 6g networks: A federated learning and multi-agent approach
    VV Teresa, J Dhanaseker, S Arjun, R Naveenraj, AA Subil, PA Najeeb
    2024 International Conference on Computing and Intelligent Reality … , 2024
    2024
    Citations: 1
  • Integrating Sentiment Analysis with Learning Analytics for Improved Student
    B Paulchamy, V Selvaraj, NM Indumathi, K Ananthi, VV Teresa
    Int. J. Comput. Exp. Sci. Eng. 10 (4) , 2024
    2024
    Citations: 6
  • Auto sorting and placing of objects using robotics vision module in melfa industrial robot
    K Mahajan, P Mane, SM Arif, KR Desai, GM Lonare, VV Teresa
    2024 5th International Conference on Mobile Computing and Sustainable … , 2024
    2024
    Citations: 3
  • Efficient Nano-Scale Design of TIEO Based Reversible Logic Toffoli Gate Priority Encoder in Quantum-Dot Cellular Automata
    K Kalpana, K Sivakami, N Revathi, SM Deepa, VV Teresa
    E3S Web of Conferences 472, 03014 , 2024
    2024
    Citations: 5
  • Reversible Logic Toffoli Gate Priority Encoder for Effective Nano-Scale Application in QCA Paradigm
    K Kalpana, B Paulchamy, VV Teresa, K Sivakami, SM Deepa, N Revathi
    International Conference on Renewable Energy, Green Computing, and … , 2023
    2023
  • LoRa enhanced real-time earthquake monitoring system for constructions using IoT and cloud
    VV Teresa, T Thamaraimanalan, S Jeevanantham, A Balaji, ...
    2023 7th International Conference on Electronics, Communication and … , 2023
    2023
    Citations: 6
  • Performance analysis of alternating minimization based low complexity detection for MIMO communication system
    M Kasiselvanathan, M Rajagopal, VV Teresa, P Krishnan
    Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i … , 2023
    2023
    Citations: 9
  • Analysis of ECG Noise Cancellation and Abnormality Classification using Various Adaptive Algorithms
    SM Ramesh, S Nithya, VV Teresa, VU Maheswari, MA Raja, ...
    2023 International Conference on Applied Intelligence and Sustainable … , 2023
    2023
    Citations: 1
  • Brain–Computer Interface-based Real-Time Movement of Upper Limb Prostheses
    K Kalpana, B Hakkem, VV Teresa, J Dhanasekar, S Ramya
    Healthcare 4.0, 185-205 , 2022
    2022
  • IoT-based underground cable fault detection
    VV Teresa, K Rajeshwaran, SS Kumar, S Vishnupriyan, S Dhanasekaran
    2022 International Conference on Augmented Intelligence and Sustainable … , 2022
    2022
    Citations: 15
  • Design and Development of movable antenna system for multiplatform wireless communication
    S Nithya, T Jagadesh, E Shalini, T Sathiyapriya, VV Teresa, ...
    2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-5 , 2022
    2022
    Citations: 7
  • Intelligent System for Monitoring Line of Safety in Railway Platforms
    M Kasiselvanathan, VV Teresa, K Sangeetha
    2022 4th International Conference on Inventive Research in Computing … , 2022
    2022
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • IoT-based underground cable fault detection
    VV Teresa, K Rajeshwaran, SS Kumar, S Vishnupriyan, S Dhanasekaran
    2022 International Conference on Augmented Intelligence and Sustainable … , 2022
    2022
    Citations: 15
  • Performance analysis of alternating minimization based low complexity detection for MIMO communication system
    M Kasiselvanathan, M Rajagopal, VV Teresa, P Krishnan
    Automatika: časopis za automatiku, mjerenje, elektroniku, računarstvo i … , 2023
    2023
    Citations: 9
  • Improved modified area efficient carry select adder (MAE-CSLA) without multiplexer
    B Anand, VV Teresa
    Journal of Computational and Theoretical Nanoscience 14 (1), 269-276 , 2017
    2017
    Citations: 9
  • Design and Development of movable antenna system for multiplatform wireless communication
    S Nithya, T Jagadesh, E Shalini, T Sathiyapriya, VV Teresa, ...
    2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon), 1-5 , 2022
    2022
    Citations: 7
  • Design of High Isolation MIMO Antennas for Ultra-Wide Band Communication
    T Sathiyapriya, V Gurunathan, J Dhanasekar, VV Teresa
    Evolution in Signal Processing and Telecommunication Networks: Proceedings … , 2022
    2022
    Citations: 7
  • Integrating Sentiment Analysis with Learning Analytics for Improved Student
    B Paulchamy, V Selvaraj, NM Indumathi, K Ananthi, VV Teresa
    Int. J. Comput. Exp. Sci. Eng. 10 (4) , 2024
    2024
    Citations: 6
  • LoRa enhanced real-time earthquake monitoring system for constructions using IoT and cloud
    VV Teresa, T Thamaraimanalan, S Jeevanantham, A Balaji, ...
    2023 7th International Conference on Electronics, Communication and … , 2023
    2023
    Citations: 6
  • An Efficient Technique for Image Compression and Quality Retrieval in Diagnosis of Brain Tumour Hyper Spectral Image
    VV Teresa, J Dhanasekar, V Gurunathan, T Sathiyapriya
    Machine Learning and Deep Learning Techniques for Medical Science, 27-44 , 2022
    2022
    Citations: 6
  • Efficient Nano-Scale Design of TIEO Based Reversible Logic Toffoli Gate Priority Encoder in Quantum-Dot Cellular Automata
    K Kalpana, K Sivakami, N Revathi, SM Deepa, VV Teresa
    E3S Web of Conferences 472, 03014 , 2024
    2024
    Citations: 5
  • Design of low power 4-bit Carry Look Ahead adder using self resetting and gate diffusion input logics
    J Dhanasekar, V Gurunathan, T Sathiyapriya, VV Teresa
    Solid State Technology 63 (6), 19142-19149 , 2020
    2020
    Citations: 5
  • Low Power Optimization of Finite Impulse Response Filter Feature Extraction by Using Thyroid Cancer Region Identification in Medical Images
    VV Teresa, B Anand
    Journal of Medical Imaging and Health Informatics 10 (1), 99-107 , 2020
    2020
    Citations: 4
  • Auto sorting and placing of objects using robotics vision module in melfa industrial robot
    K Mahajan, P Mane, SM Arif, KR Desai, GM Lonare, VV Teresa
    2024 5th International Conference on Mobile Computing and Sustainable … , 2024
    2024
    Citations: 3
  • Intelligent System for Monitoring Line of Safety in Railway Platforms
    M Kasiselvanathan, VV Teresa, K Sangeetha
    2022 4th International Conference on Inventive Research in Computing … , 2022
    2022
    Citations: 3
  • Error tolerant modified booth multiplier for lossy applications
    NR Thomas, VV Teresa
    Int. J. Modern Eng. Res.(IJMER) 2 (3), 1125-1128 , 2012
    2012
    Citations: 2
  • A hybrid approach for soil classification: integrating lightweight convolutional neural network, attention mechanisms, and color features under resource constraints
    SK Behera, S Vishwakarma, VV Teresa, AK Ratha, PK Sethy, ...
    Proceedings of the Indian National Science Academy, 1-10 , 2025
    2025
    Citations: 1
  • Thermal vision for lady finger quality assessment: a three-stage convolutional neural network approach
    SK Behera, PBS Varma, VV Teresa, K Das, PK Sethy, ...
    International Journal of Food Science and Technology 60 (2), vvaf171 , 2025
    2025
    Citations: 1
  • Ai-enhanced security architecture for 6g networks: A federated learning and multi-agent approach
    VV Teresa, J Dhanaseker, S Arjun, R Naveenraj, AA Subil, PA Najeeb
    2024 International Conference on Computing and Intelligent Reality … , 2024
    2024
    Citations: 1
  • Analysis of ECG Noise Cancellation and Abnormality Classification using Various Adaptive Algorithms
    SM Ramesh, S Nithya, VV Teresa, VU Maheswari, MA Raja, ...
    2023 International Conference on Applied Intelligence and Sustainable … , 2023
    2023
    Citations: 1
  • A blockchain-driven intrusion detection model for secure communication in IoT-WSN mesh architectures
    G Elumalai, JA Kumar, P Sivakumar, VV Teresa
    Peer-to-Peer Networking and Applications 19 (2), 60 , 2026
    2026
  • Cross-Technology Evaluation of a Gate-Diffusion-Input Magnitude Comparator for Scalable CMOS Architectures
    VV Teresa, AN Duraivel, MS Kokilamani
    INTERNATIONAL JOURNAL OF ADVANCES IN SIGNAL AND IMAGE SCIENCES, 104-123 , 2026
    2026