Publications | Thiagarajar College of Engineering

S.No	2021 – 26 JOURNALS (APA)
1	Rasina Begum, B., & Chitra, P. (2021). ECC-CRT: an elliptical curve cryptographic encryption and Chinese remainder theorem based deduplication in cloud. Wireless Personal Communications, 116(3), 1683-1702.
2	Malini, A., Priyadharshini, P., & Sabeena, S. (2021). An automatic assessment of road condition from aerial imagery using modified VGG architecture in faster-RCNN framework. Journal of Intelligent & Fuzzy Systems, 40(6), 11411-11422.
3	Alagarsamy, M., Sundarji, A., Arunachalapandi, A., & Kalyanasundaram, K. (2021). Cost-aware ant colony optimization based model for load balancing in cloud computing. Int. Arab J. Inf. Technol., 18(5), 719-729.
4	Lilian, J. F., Sundarakantham, K., & Shalinie, S. M. (2021). Anti-negation method for handling negation words in question answering system. The Journal of Supercomputing, 77, 4244-4266.
5	Abirami, S., & Chitra, P. (2021). Regional air quality forecasting using spatiotemporal deep learning. Journal of cleaner production, 283, 125341.
6	Sriram, S., Dwivedi, A. K., Chitra, P., Sankar, V. V., Abirami, S., Durai, S. R., ... & Khare, M. K. (2022). Deepcomp: A hybrid framework for data compression using attention coupled autoencoder. Arabian Journal for Science and Engineering, 47(8), 10395-10410.
7	Sivasundaram, S., & Pandian, C. (2021). Performance analysis of classification and segmentation of cysts in panoramic dental images using convolutional neural network architecture. International Journal of Imaging Systems and Technology, 31(4), 2214-2225.
8	Lilian, J. F., Sundarakantham, K., & Shalinie, S. M. (2021). QeCSO: Design of hybrid Cuckoo Search based Query expansion model for efficient information retrieval. Sādhanā, 46(3), 181.
9	Kanth, A. K., Chitra, P., & Sowmya, G. G. (2022). Deep learning-based assessment of flood severity using social media streams. Stochastic Environmental Research and Risk Assessment, 36(2), 473-493.
10	Alagarsamy, M., &Sathik, A. S. (2022). Context aware mobile application pre-launching model using KNN classifier. Int. Arab J. Inf. Technol., 19(6), 932-941.
11	Sivakumar, M., Renuka, P., Chitra, P., & Karthikeyan, S. (2022). IoT incorporated deep learning model combined with SmartBin technology for real‐time solid waste management. Computational Intelligence, 38(2), 323-344.
12	Abirami, S., & Chitra, P. (2022). Regional spatio-temporal forecasting of particulate matter using autoencoder based generative adversarial network. Stochastic Environmental Research and Risk Assessment, 36(5), 1255-1276.
13	Abirami, S., & Chitra, P. (2023). Probabilistic air quality forecasting using deep learning spatial–temporal neural network. GeoInformatica, 27(2), 199-235.
14	Sriram, S., Chitra, P., Sankar, V. V., Abirami, S., & Durai, S. R. (2023). Low-loss data compression using deep learning framework with attention-based autoencoder. International Journal of Computational Science and Engineering, 26(1), 90-100.
15	Rasina Begum, B., & Chitra, P. (2023). SEEDDUP: a three-tier SEcurE data DedUPlication architecture-based storage and retrieval for cross-domains over cloud. IETE Journal of Research, 69(4), 2224-2241.
16	Suganthi, P., & Kavitha, R. (2023). Secure and privacy in healthcare data using quaternion based neural network and encoder-elliptic curve deep neural network with blockchain on the cloud environment. Sādhanā, 48(4), 206
17	Suganthi, P., & Kavitha, R. (2023). Secure and privacy in healthcare data using quaternion-based neural network cryptography with the blockchain mechanism. IETE Journal of Research, 69(10), 6997-7014.
18	P., S. ., A., M. ., Lilian J., F. ., &Vetriveeran, D. . (2023). Blockchain-Based Service Oriented Privacy-Preserving Data Sharing over Distributed Data Streams in Asynchronous Environment. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 591–602.
19	Lilian, J. F. ., Vetriveeran, D. ., Malini, A. ., & Kayalvizhi, S. . (2023). HQA Bot: Hybrid AI Recommender Based Question Answering Chatbot. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 227–233.
20	Abirami, S., Pethuraj, M., Uthayakumar, M., & Chitra, P. (2024). A systematic survey on big data and artificial intelligence algorithms for intelligent transportation system. Case Studies On Transport Policy, 101247.
21	Srivathsan, K., Bharath, S., Malini, A., Kumaravel, R., & Sharma, V. (2024). Extended virtual reality based memory enhancement model for autistic children using linear regression. International Journal of System Assurance Engineering and Management, 1-11.
22	Siva, T., & Merline, A. (2024). Optimizing network lifetime: ERBS-REE for resilient object detection and tracking in resource-constrained WSN environments. Signal, Image and Video Processing, 18(6), 5189-5201.
23	Muraleedhara, P., Christo, M. S., Jaya, J., & Yuvasini, D. (2024). Any bluetooth device can be hacked. know how?. Cyber Security and Applications, 2, 100041.
24	Jeba, G. S., & Chitra, P. (2024). Flood prediction through hydrological modeling of rainfall using Conv1D-SBiGRU algorithm and RDI estimation: A hybrid approach. Stochastic Environmental Research and Risk Assessment, 38(9), 3587-3606.
25	Selva Jeba, G., & Chitra, P. (2024). River flood prediction through flow level modeling using multi-attention encoder-decoder-based TCN with filter-wrapper feature selection. Earth Science Informatics, 1-17.
26	Abirami, S., Pethuraj, M., Uthayakumar, M., & Chitra, P. (2024). A systematic survey on big data and artificial intelligence algorithms for intelligent transportation system. Case Studies On Transport Policy, 101247.
27	Rajalakshmi, J., Guruprakash, B., Siva, T., & Murugan, S. Deep Learning-Assisted Electromagnetic Simulations For Enhanced Microstrip Circuit Design Using Recurrent Neural Networks.
28	Yuvasini, D., Jegadeesan, S., Selvarajan, S., & Mon, F. A. (2024). Enhancing societal security: a multimodal deep learning approach for a public person identification and tracking system. Scientific Reports, 14(1), 23952.
29	Guru Prakash B, Siva T, Shunmugasundaram S, Mariappan E, Anna Lakshmi A, Ramnath Muthusamy (2025). Next-Gen Security: Leveraging DNA Cryptography For Robust Encryption. Journal Of Theoretical And Applied Information Technology, 103(10).
30	J Jagadeesan, M. Azhagiri, And M Gowtham Sethupathi, “Touchless Atm Using Augmented Reality Using TOTP Haar Cascade Algorithm”, Ijsce, Vol. 15, No. 1, Pp. 5–9, Mar. 2025, Doi: 10.35940/Ijsce.F3506.15010325.
31	Sethupathi, M. G., & Azhagiri, M. (2024). A Hybrid Model Combining Improved Weighted Wolf Optimization And Reinforcement Learning For Estimating Electric Vehicle Travel Time. Sn Computer Science, 5(8), 1049.
32	Rajkumar, S. C., Cirillo, S., Yuvasini, D., & Solimando, L. (2025). A hybrid approach combining images and questionnaires for early detection and severity assessment of Autism Spectrum Disorder. Image and Vision Computing, 160, 105547.
33	Karthiga, S., Indira, K., Angeline, C. N., & Kamala, J. (2026). Secure Handover and Authentication for Intrusion Prevention in Mobile Sensor Wireless Networks. Journal of Electrical Engineering & Technology, 1-10.
34	Rajkumar, S. C., Yuvasini, D., Selvarajan, S., & Sivakumar, N. R. (2025). A zero-shot LLM framework for multimodal grievance classification, urgency scoring, and abuse detection in civic feedback systems. Scientific Reports.
35	Yuvasini, D., &Jegadeesan, S. (2026). Adversarially-robust multi-biometric fusion with semantic-aware decision making for home intruder detection. Egyptian Informatics Journal, 34, 100942.
2021 – 26 EDITED BOOKS
1	Devi, M. K., Murugan, T., Indira, K., Lavanya, R., & Abinaya, S. (Eds.). (2026). Intelligent Mobile and IoT Ecosystems: Bridging Cloud, Fog, Edge, and AI. CRC Press.
2	Alagarsamy, M., Dhanaraj, R. K., Lilian, J. F., Sharma, V., & Ghinea, G. (Eds.). (2026). Graph Convolutional Neural Networks for Computer Vision. John Wiley & Sons.
2021 – 26 BOOK CHAPTERS (APA)
1	Abirami, S., & Chitra, P. (2020). Energy-efficient edge based real-time healthcare support system. In Advances in computers (Vol. 117, No. 1, pp. 339-368). Elsevier.
2	Asok, D., Chitra, P., &Muthurajan, B. (2021). Privacy Preserving Machine Learning and Deep Learning Techniques: Application–E-Healthcare. In Research Anthology on Privatizing and Securing Data (pp. 1621-1634). IGI Global.
3	Chitra, P., & Abirami, S. (2022). Smart pollution alert system using machine learning. In Research Anthology on Machine Learning Techniques, Methods, and Applications (pp. 1072-1085). IGI Global Scientific Publishing.
4	Abirami, S., & Pandian, C. (2022). IoT and FOG space-time Particulate Matter (PM2. 5) concentration forecasting for IoT-based air pollution monitoring systems. In Internet of Things and Fog Computing-Enabled Solutions for Real-Life Challenges (pp. 61-84). CRC Press.
5	Kiruthiga, A. S., Arunkumar, S., Thirisha, R., & Lilian, J. F. (2023). Role of machine learning in renewable energy. In Sustainable Energy Solutions with Artificial Intelligence, Blockchain Technology, and Internet of Things (pp. 47-65). CRC Press.
6	Sriram, G. K., Rajasekaran, U., & Malini, A. (2023). CNN Architecture and Classification of Miosis and Mydriasis Clinical Conditions. In Artificial Intelligence in IoT and Cyborgization (pp. 125-134). Singapore: Springer Nature Singapore.
7	Malini, A., Ramyavarshini, P., Sriram, G. K., & Rajasekaran, U. (2023). Role of Object Detection for Brain Tumor Identification Using Magnetic Resonance Image Scans. In Artificial Intelligence in IoT and Cyborgization (pp. 135-153). Singapore: Springer Nature Singapore.
8	Jeba, G. S., & Chitra, P. (2024). Exploring the Power of Deep Learning and Big Data in Flood Forecasting: State-of-the-Art Techniques and Insights. In Intelligent Systems and Sustainable Computational Models (pp. 14-33). Auerbach Publications.
9	Kaviya, P., & Chitra, P. (2024). Hydro-Meteorological Disaster Prediction Using Deep Learning Techniques. In Intelligent Systems and Sustainable Computational Models (pp. 61-81). Auerbach Publications.
10	Suguna, M., & Thiagarajan, P. (2023). Deep learning applications in ophthalmology—computer-aided diagnosis. Deep Learning in Medical Image Processing and Analysis, 237. IET, United Kingdom
11	Malini, A., Rajasekaran, U., Sriram, G. K., &Ramyavarshini, P. (2023). Industry 4.0: survey of digital twin in smart manufacturing and smart cities. In Digital Twin for Smart Manufacturing (pp. 89-110). Academic Press.
12	Sriram, G. K., Malini, A., & Santhosh, K. M. R. (2024). State of the art of artificial intelligence approaches toward driverless technology. Artificial Intelligence for Autonomous Vehicles, 55-74.
13	Rajasekaran, U., Malini, A., & Murugan, M. (2024). Artificial Intelligence in Autonomous Vehicles—A Survey of Trends and Challenges. Artificial Intelligence for Autonomous Vehicles, 1-24.
14	Ramyavarshini, P., Malini, A., & Mahalakshmi, S. (2024). A Survey on Architecture of Autonomous Vehicles. Artificial Intelligence for Autonomous Vehicles, 75-103.
15	Anjana Devi, R., Harshini Amutha, V., & Thiagarajan, Priya. (2025). Unmanned Aerial Vehicles Enabled IoT Platform for Effective Disaster Management. Machine Learning for Drone-Enabled IoT Networks, 1-17. Springer.
16	Thilagavathy, J. J. P., Lilian, J. F., & Malini, A. (2025). Polarizing Sentiments: A Comprehensive Analysis of Social Media Content Using Text Extraction and Sentiment Polarization. In Advanced AI and Data Science Applications (pp. 105-118). Auerbach Publications.
17	Suguna, M., & Thiagarajan, P. (2025). Analysis and Classification Using Graph Convolutional Neural Networks in Medical Imaging. Graph Convolutional Neural Networks for Computer Vision, 205-224.
18	Rithish Kanna, S., Suganthi, P., & Kavitha, P. (2025). Research Trends and Challenges of GCNN Over CNN and Digital Image Processing Techniques. Graph Convolutional Neural Networks for Computer Vision, 73-94.
2021 – 26 CONFERENCE PAPERS (APA)
1	Vijay Sankar, V., Chitra, P., & Poonkuzhali, B. (2021). WattCastLSTM—Power Demand Forecasting Using Long Short-Term Memory Neural Network. In Innovations in Sustainable Energy and Technology: Proceedings of ISET 2020 (pp. 1-11). Springer Singapore.
2	Malini, A., Yugakiruthika, A. B., Gunasekar, S. P., & Preethi, R. (2021, January). Testing as a service focused on semantic interoperability: An approach. In 2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-5). IEEE.
3	Leena, S. R., Divya, V., & Lilian, J. F. (2020, November). Intelligent scheduling in fog environment based on improved hybrid heuristics. In 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA) (pp. 1-7). IEEE.
4	Yugakiruthika, A. B., & Malini, A. (2022). Security testing for blockchain enabled IoT system. In Data Engineering for Smart Systems: Proceedings of SSIC 2021 (pp. 45-55). Springer Singapore.
5	Yugakiruthika, A. B., & Malini, A. (2022). A comprehensive tool survey for blockchain to IoT applications. In Data Engineering for Smart Systems: Proceedings of SSIC 2021 (pp. 89-99). Springer Singapore.
6	Shanthini, K. M., Chitra, P., Abirami, S., Aninthitha, G., & Abarna, P. (2021, July). Recommendation of product value by extracting expiry date using deep neural network. In 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-7). IEEE.
7	Chitra, P., & Abirami, S. (2022, March). A deep learning ensemble model for short-term rainfall prediction. In 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET) (pp. 135-138). IEEE.
8	Chitra, P., & Rajasekaran, U. M. (2022, March). Time-series analysis and flood prediction using a deep learning approach. In 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET) (pp. 139-142). IEEE.
9	Ramyavarshini, P., Sriram, G. K., Rajasekaran, U., & Malini, A. (2022, December). Explainable AI for intrusion detection systems. In 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 1563-1567). IEEE.
10	Thanush, A. A., Chitra, P., Kasinath, J., & Prakash, R. S. (2022, July). Atmospheric corrosion rate prediction of low-alloy steel using machine learning models. In IOP Conference Series: Materials Science and Engineering (Vol. 1248, No. 1, p. 012050). IOP Publishing.
11	Gokul Raj, S. N., Chitra, P., Silesh, A. K., & Lingeshwaran, R. (2022, March). Flood severity assessment using distilbert and ner. In International Conference on Machine Intelligence and Signal Processing (pp. 391-402). Singapore: Springer Nature Singapore.
12	Sriram, G. K., Karunasagar, A., & Sudharsan, R. (2023, February). Deep learning approaches for Pneumonia classification in healthcare. In 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 1-6). IEEE.
13	Srivathsan, K., Bharath, S., Kumaravel, R., Vishnu Prasad, V., & Malini, A. (2023, February). Customization of User Experience in Fashion Technology. In 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 1-6). IEEE.
14	Rajasekaran, U., Sriram, G. K., Ramyavarshini, P., & Malini, A. (2023, February). XAI-Based Light-Weight CNN-HAR Model Using Random Sampling. In International Conference on Emerging Trends and Technologies on Intelligent Systems (pp. 377-388). Singapore: Springer Nature Singapore.
15	Harshitha, P., Nafiza, R., Lilian, J. F., & Malini, A. (2023, May). Exploring the potential of machine learning for early diagnosis of Parkinson's disease: A comparative study. In 2023 4th International Conference on Intelligent Engineering and Management (ICIEM) (pp. 1-6). IEEE.
16	Bhagampriyal, M., Gowtham, R., Johnson, J., Lilian, J. F., & Suganthi, P. (2023, February). Recommendation Systems for Supermarket. In 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 1-6). IEEE.
17	Sachin, K., Santhosh, K. M. R., Srinivas Karthik, D., Vaseekaran, M., Felicia Lilian, J., & Suganthi, P. (2023, February). I-PWA: IoT based Progressive Web Application For Visually Impaired People. In 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM) (pp. 1-6). IEEE.
18	Thiagarajan, Priya, & Suguna, M. (2023, June). Deep learning ocular disease detection system (ODDS). In International Conference on Mining Intelligence and Knowledge Exploration (pp. 213-224). Cham: Springer Nature Switzerland.
19	Bennet, D. T., Bennet, P. S., & Thiagarajan, P. (2024, February). Content Based Classification of Short Messages using Recurrent Neural Networks in NLP. In 2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) (pp. 1-6). IEEE.
20	Arunkumar, S., Thirisha, R., Kiruthiga, S., Lilian, J. F., & Malini, A. (2023, September). Gender and Age Classification Using Caffe Network. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 950-954). IEEE.
21	Nagaesvara, E. B. R., Aadhithya, M., & Malini, A. (2023, September). An Analysis of Machine Learning Techniques for Forest Cover Type Classification. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 489-494). IEEE.
22	Chitra, P. (2023, August). Flood Detection from Satellite Images Using Self-Attention Empowered EfficientNetV2 Mechanism. In 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA) (pp. 1-4). IEEE.
23	Chitra, P., Sree, H., Subbulakshmi, P., & Umayal, C. (2023, August). A Hybrid Flood Forecasting Approach Using Hidden Markov Model and Machine Learning Techniques. In 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA) (pp. 1-5). IEEE.
24	Nandhini, S., Vaishnavi, M. S., Meenaragavi, P., & Felicia Lilian, J. (2023, December). Detecting of Road Signs with Neural Networks. In 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (Vol. 10, pp. 642-646). IEEE.
25	Janakiraman, V., & Chitra, P. (2024, June). Wind Speed Forecasting using Deep Learning. In 2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC) (pp. 250-254). IEEE.
26	Venkatachalam, M., Chitra, P., & Thiagarajan, P. (2024, December). Comm-bot: Generative AI for Optimising Supply Chains integrating LSTM with LLMs. In 2024 IEEE 31st International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW) (pp. 209-210). IEEE.
27	Akshara, A., Chitra, P., & Sahana, S. (2024, February). Exploring Corrosion Detection: Deep Learning and Ensemble Approaches Analysis. In International Conference on Computational Intelligence in Data Science (pp. 136-155). Cham: Springer Nature Switzerland.
28	Kumar, K. S., Rathinavel, S. D., Raghavendharan, M., & Lilian, F. (2024, June). Enforcing Image Encryption using Cryptographic Algorithms. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
29	Jothir Adithya T K, Nithish Kumar S, Felicia Lilian J, Mahalakshmi S (2024, December). Monolingual text summarization for Indic Languages using LLMs. In Proceedings of the 21st International Conference on Natural Language Processing (ICON) (pp. 94-101).
30	Viswadarshan, R. R., & Mahalakshmi, S. (2024, December). Enhancing Masked Word Prediction in Tamil Language Models: A Synergistic Approach Using BERT and SBERT. In Proceedings of the 21st International Conference on Natural Language Processing (ICON) (pp. 472-480).
31	Pargavi, N., Abirami, K., & Suganthi, P. (2024). Limitations of Visually Impaired. In Perspective and Strategies on Newage Education and Creative Learning: Proceedings of 2nd International Conference on Best Innovative Teaching Strategies, BITS Pilani (p. 3). Springer Nature.
32	Anushri, T., Bhavadharani, B. N., & Suganthi, P. (2024, September). Crop Recommendation and Yield Prediction using Machine learning and Deep learning models. In 2024 International Conference on Integration of Emerging Technologies for the Digital World (ICIETDW) (pp. 1-6). IEEE.
33	Shrinivas, S., & Varun, G. K. (2024, August). Integrating AES-GCM, ECC, and Steganography for Enhanced Confidential Communication. In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) (Vol. 1, pp. 1-7). IEEE.
34	Thiagarajan, P. (2024, October). Intelligent Water Body Delineation for Flood Monitoring Using Remote Sensing Data and Deep Learning Algorithms. In 2024 4th International Conference on Artificial Intelligence and Signal Processing (AISP) (pp. 01-05). IEEE.
35	Selvaraj, A., & Selvi, S. T. T. (2025, August). A proposed hybrid walrus gazelle optimization for feature selection in intrusion detection systems. In 2025 International Conference on Next Generation Computing Systems (ICNGCS) (pp. 1-6). IEEE.
36	Janakiraman, V., Sachin, K., Johnson, J., & Chitra, P. (2025, August). Uncertainty-Aware Wind Speed Forecasting: A GLUE-Based Hybrid Ensemble Approach. In 2025 International Conference on Next Generation Computing Systems (ICNGCS) (pp. 1-7). IEEE.
37	Yuvasini, D., Rajkumar, S. C., Natesan, D., Balusamy, B., & Tanwar, S. (2024, November). Empowering Lives: A Revolutionary IoT-Driven Communication System for Paralytic and Disabled Patients. In International Conference on Emerging Technologies: Micro to Nano (pp. 993-1008). Cham: Springer Nature Switzerland.
38	Mahalakshmi, P. P., & Mahalakshmi, S. (2025, April). Enhancing Digital Integrity with Hybrid Deepfake Detection for Images and Videos. In 2025 International Conference on Data Science and Business Systems (ICDSBS) (pp. 1-6). IEEE.
39	MSS, Manish Raj, Harshini, N., Lilian, J. F., & Malini, A. (2025). Heart disease detection using novel ensemble approach: RF-GB-SVM stacking classifier. Procedia Computer Science, 258, 2647-2658.
40	Sathyavani, M., & Devi, M. K. (2025, January). Plastic Type Classification for Edge Devices Without Internet. In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) (pp. 1-4). IEEE.
41	LCK, Shri Vaisalini, & Devi, M. K. (2025, January). Real Time Traffic Light Timing Optimisation Using Reinforcement Learning. In 2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) (pp. 1-4). IEEE.
42	Akash, K., Jilvis, J. J., Lilian, J. F., &Subhashni, R. (2025, January). Blockchain Technology for Strengthening Content Protection in E-Voting. In International Conference on Smart Trends for Information Technology and Computer Communications (pp. 437-447). Singapore: Springer Nature Singapore.
43	Mahalakshmi, S., & Lilian, J. F. (2025, February). Domain-Specific Paraphrase Identification for Tamil Using SBert Models. In International Conference on Computational Intelligence in Data Science (pp. 15-28). Cham: Springer Nature Switzerland.
44	Viswadarshan, R. R., Viswaa Selvam, S., Felicia Lilian, J., & Mahalakshmi, S. (2025, February). Comparative Insights into Modern Architectures for Paraphrase Detection. In International Conference on Computational Intelligence in Data Science (pp. 354-379). Cham: Springer Nature Switzerland.
45	Muthupalaniappaa M N; Gideon Samuel M; Suganthi P, (2025, December). Cardiovascular Disease Detection Using Retinal Fundus Images. In 2025 IEEE 4th International Conference on Data, Decision and Systems (ICDDS) (pp. 78-83). IEEE.
46	Tamilnilavan, K., Eswar, V., & Venkatesh, M. (2025, December). AI/DL Map-Matching for Highway and Service Road Distinction. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1729-1734). IEEE.
47	Venkatesh, M., Chitra, P., Dharini, A., Umayal, C., & Kiruthika, B. (2025, December). PCOS-GPT: A RAG Enhanced LLM for Personalized Ultrasound Based PCOS Diagnosis. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 599-605). IEEE.
48	Kaaviyaa, I., Madhubala, M., Suganthi, P., Logitha, K., & Janakiraman, V. (2025, April). IoT and Machine Learning-Integrated Approach for Accurate Forest Fire Detection. In International Conference on Green Artificial Intelligence and Industrial Applications (pp. 352-363). Cham: Springer Nature Switzerland.
49	Navina, M., Mazwin Asra, A., Suganthi, P., & Janakiraman, V. (2025, April). Wind Speed Prediction Using Deep Learning. In International Conference on Green Artificial Intelligence and Industrial Applications (pp. 376-384). Cham: Springer Nature Switzerland.
50	Gayathri, G., Visaka, P., & Chitra, P., Thiagarajan, P. (2025, November). Enhancing Healthcare Waste Management Through Deep Learning-Based Classification. In 2025 International Conference on Intelligent & Innovative Practices in Engineering & Management (IIPEM) (pp. 1-6). IEEE.
51	Jeyasakthi, R., Kavyaa, S. M., &Mivetha, K. Thiagarajan, P., Chitra. P. (2025, November). Explainable AI for Early Detection and Characterization of Retinal Pathologies in OCT. In 2025 International Conference on Intelligent & Innovative Practices in Engineering & Management (IIPEM) (pp. 1-5). IEEE.
52	Praveen Kumar, R., Thiagarajan, P. (2025, November). ML and DL Based Approach to Predict and Detect Forest Fire Risk Management. In 2025 International Conference on Intelligent & Innovative Practices in Engineering & Management (IIPEM) (pp. 1-6). IEEE.