Publications

Recent publications (2023-):

A. Mundayatt and J. Sreevalsan-Nair, “Scaling up Study Area Size in Flood Susceptibility Mapping,” in Proceedings of 2024 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (accepted), IEEE, 2024.
S. Mathai, P. Krishnan, and J. Sreevalsan Nair, “Understanding Graphical Literacy Using School Students’
Comprehension Strategies,” Contemporary Education Dialogue (accepted), March 2024.
L. S. Liang, J. Sreevalsan-Nair, and B. S. D. Sagar, “Multispectral Data Mining: A Focus on Remote Sensing Satellite Images,” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1522, October 2023. (doi)(eprint)

J. Sreevalsan-Nair, A. Mubayi, J. Chhabra, R. R. Vangimalla, and P. R. Ghogale, “Evaluating Early Pandemic Response through Length-of-Stay Analysis of Case Logs and Epidemiological Modeling: A Case Study of Singapore in Early 2020,” Computational and Mathematical Biophysics, vol. 11, no. 1, p. 20 230 104, October 2023. (doi)(open access)

P. Rastogi, K. Singh, and J. Sreevalsan-Nair, “SunburstChartAnalyzer: Hierarchical Data Retrieval from Images of Sunburst Charts for Tree Visualization,” in Computer Graphics & Visual Computing (CGVC), P. Vangorp and D. Hunter, Eds., The Eurographics Association, 2023, pp. 97–101, ISBN: 978-3-03868-231-8. (doi)


L.-T. Tay and J. Sreevalsan-Nair, “Disaster Susceptibility Analysis in Remote Sensing,” in Cognitive Sensing Technologies and Applications, G. R. Sinha, B. Subudhi, C.-P. Fan, and H. Nisar, Eds., Stevenage, UK: Institute of Engineering and Technology (IET), 2023 (doi)(url).

D. Katkoria and J. Sreevalsan-Nair, “Evaluating and Improving RoSELS for Road Surface Extraction from 3D Automotive LiDAR Point Cloud Sequences,” in Deep Learning Theory and Applications: Revised Selected Papers from Third International Conference DeLTA 2022, Portugal, Chapter 6, CCIS volume 1858, Springer Cham, 2023. (doi) (book-link)

B. Gnanaraj and J. Sreevalsan-Nair, “EyeExplore: An Interactive Visualization Tool for Eye-Tracking Data for Novel Stimulus-Based Analysis,” in Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, ser. ETRA ’23, Tubingen, Germany: ACM, 2023. (doi)

J. Sreevalsan-Nair, Co-Association Matrices in Ensemble Clustering: Diverse Applications and Extensions, Preprint available at SSRN, May 2023. (url)

H. Ravindra and J. Sreevalsan-Nair, “A Methodology for Integrating Population Health Surveys Using Spatial Statistics and Visualizations for Cross-sectional Analysis,” SN Computer Science, vol. 4, no. 224, pp. 1–19, 2023. (full-text view) (doi)

S. Singh and J. Sreevalsan-Nair, “Visual Exploration of LiDAR Point Clouds,” in Advances in Scalable and Intelligent Geospatial Analytics: Challenges and Applications, Chapter 12, K. Kurte, S. Durbha, J. Sanyal, L. Yang, S. Chaudhari, U. Bhangale, and U. Bharambe, Eds., Florida, USA: CRC Press, 2023, p. 19. (doi)

J. Sreevalsan-Nair, “On Metavisualization and Properties of Visualization,” in Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Vol 3, IVAPP, INSTICC, SciTePress, 2023, pp. 230–239, ISBN: 978-989-758-634-7. (doi)



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J. Sreevalsan-Nair, K. Dadhich, and S. C. Daggubati, "Tensor Fields for Data Extraction from Chart Images: Bar Charts and Scatter Plots," in Topological Methods in Data Analysis and Visualization VI, Ingrid Hotz, Talha Bin Masood, Filip Sadlo, and Julien Tierny (Eds.). Springer, Cham, 2021, pp 219-241. (doi). Preprint at arXiv (2020), October 2020, https://arxiv.org/abs/2010.02319