International Journals
Sreelakshmi, S., Vinod Chandra, S. S., Ali Daud, and Tariq Alsahfi, “Multilayer Pyramid Pooling Transformer for Landslide Detection,” Scientific Reports, Nature (Accepted for Publication - IF: 3.9, Q1).
V. S. Anoop, S. Sreelakshmi, “AutoCrack: Deep Transformer with Pyramid Pooling for Autonomous Pavement Crack Identification”, Applied Computational Intelligence and Soft Computing, Wiley (SCIE, IF: 2.9, Q1).
Amal Krishnan, S. Sreelakshmi, Vinod Chandra S. S., Shaji E., “Prediction of Tropical Cyclone Categories in North-Western Pacific Using Long Short Term Memory Network”, Frontiers in Earth Science (SCIE, IF: 2.0, Q2).
Sreelakshmi, S., Vinod Chandra, S. S., “LanXensemble: Explainability Enabled Landslide Susceptibility Prediction,” International Journal of Data Science and Analytics, Springer (ESCI, IF: 2.8, Q2).
Sreelakshmi, S., Vinod Chandra, S. S., “A Hybrid Fusion Network using Convolutional Vision Transformers for Landslide Identification,” Expert Systems With Applications, Elsevier (2025): 129688. (SCIE, IF: 7.5, Q1).
Sreelakshmi, S., & Chandra, S. V. (2025). LanPPT: Enhancing landslide crack detection through pyramid pooling transformers. Applied Soft Computing, Elsevier (2025): 113765. (SCIE, IF: 6.6, Q1)
Sreelakshmi, S., and SS Vinod Chandra. ”Visual saliency-based landslide identification using super-resolution remote sensing data.” Results in Engineering, Elsevier, 21 (2024):101656. (ESCI, IF: 7.9, Q1)
Babu, Manisha S., S. Sreelakshmi, Vinod Chandra S. S., V. Sunitha, and E. Shaji. ”Advancing Water Quality Assessment and Monitoring with a Robust Stacked Ensemble Method.” Water Resources Management, Springer (2024): 1-19. (SCIE, IF: 4.9, Q1)
Anoop, V. S., & Sreelakshmi, S. ”Public discourse and sentiment during Mpox outbreak: an analysis using natural language processing”. Public Health, Elsevier, 218 (2023), 114-120. (IF: 3.2, Q1)
Sreelakshmi, S., & Malu, G. ”M-Net: An encoder-decoder architecture for medical image analysis using ensemble learning”. Results in Engineering, Elsevier, 17 (2023): 100927. (ESCI, IF: 7.9, Q1)
Sreelakshmi, S., Vinod Chandra, and E. Shaji, ”Landslide identification using machine learning techniques: Review, motivation, and future prospects.” Earth Science Informatics, Springer, 15.4 (2022): 2063-2090. (SCIE, IF: 3.0, Q2)
Sreelakshmi, S., Vinod Chandra, S. S., “Landslide Detection Using Convolutional Vision Transformers: A Hybrid Deep Learning Approach,” Artificial Intelligence in Geoscience, Elsevier (Under Revision).
International Conferences
Sreelakshmi, S., and Vinod Chandra, S. S. (2025). "An Enhanced Feature Extraction Technique for Landslide Image Analysis." 11th International Conference on Smart Computing and Communications (ICSCC 2025), IEEE (Scopus Indexed)
Faisal, G., Sreelakshmi, S., Vinod Chandra S. S. (2023). Crop yield prediction for smart agriculture with climatic parameters using random forest. In International Conference on Advances in Computing and Data Sciences (pp. 367-376). Cham: Springer Nature Switzerland. (Scopus Indexed)
Sreelakshmi, S., Vinod Chandra, S. S. (2023). Landslide classification using deep convolutional neural network with synthetic minority oversampling technique. In International Conference on Distributed Computing and Intelligent Technology (pp. 240-252). Cham: Springer Nature Switzerland. (Scopus Indexed)
Sreelakshmi, S., Vinod Chandra, and E. Shaji. ; Machine Learning for Landslide Risk Analysis: An Overview, International conference on Landslide Risk Reduction (ICLRR 2022), Proceedings of ICLRR 2022: 72-77 (ISBN No: 978-81-958462-9-0)
Sreelakshmi, S., Vinod Chandra S.S. (2022). Machine learning for disaster management: insights from past research and future implications. In 2022 International Conference on Computing, Communication, Security, and Intelligent Systems (IC3SIS) (pp. 1-7). IEEE. (Scopus Indexed)
Sreelakshmi, S., Malu, G. (2022). Alzheimer’s disease classification from cross-sectional brain MRI using deep learning. In 2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES) (Vol.1, pp. 401-405). IEEE. (Scopus Indexed)
Sreelakshmi, S., Mathew, R. (2022). A Hybrid Approach for Classifying Parkinson’s Disease from Brain MRI. In Proceedings of International Conference on Information Technology and Applications: ICITA 2021 (pp. 171-181). Singapore: Springer Nature Singapore. (Scopus Indexed)
Book Chapters
Sreelakshmi, S., Anoop, V. S. (2021). Prediction of neurological disorders using visual saliency: Current trends and future directions. In Machine learning and data analytics for predicting, managing, and monitoring disease (pp. 1-11). IGI Global. (Scopus Indexed)
Sreelakshmi, S., Vinod Chandra S. S. (2022). Blockchain technology in disaster management: A high-level overview and future research dimensions. In Blockchain for Industry 4.0 (pp. 229-243). CRC Press. (Scopus Indexed)