| The Schrödinger distance transform (SDT) for point-sets and curves M Sethi, A Rangarajan, K Gurumoorthy 2012 IEEE Conference on Computer Vision and Pattern Recognition, 198-205, 2012 | 24 | 2012 |
| Scalable machine learning approaches for neighborhood classification using very high resolution remote sensing imagery M Sethi, Y Yan, A Rangarajan, RR Vatsavai, S Ranka Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 21 | 2015 |
| Graph-based semi-supervised classification on very high resolution remote sensing images Y Yan, M Sethi, A Rangarajan, RR Vatsavai, S Ranka International Journal of Big Data Intelligence 4 (2), 108-122, 2017 | 12 | 2017 |
| Supervoxel-based segmentation of 3d volumetric images C Yang, M Sethi, A Rangarajan, S Ranka Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 11 | 2017 |
| An efficient computational framework for labeling large scale spatiotemporal remote sensing datasets M Sethi, Y Yan, A Rangarajan, RR Vatsavaiy, S Ranka 2014 Seventh International Conference on Contemporary Computing (IC3), 635-640, 2014 | 8 | 2014 |
| Super-scalable computation framework for automated terrain identification Y Yan, M Sethi, A Rangarajan, S Ranka 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th …, 2017 | 2 | 2017 |
| Validating an sfm map using lidar point clouds KA Desai, X Xinjilefu, G Pan, M Sethi, TV Fu US Patent 20230128756A1, 2023 | 1 | 2023 |
| Image stack surface area minimization for groupwise and multimodal affine registration BH Guan, J Corring, M Sethi, S Ranka, A Rangarajan 2016 23rd International Conference on Pattern Recognition (ICPR), 4196-4201, 2016 | 1 | 2016 |
| A computational framework for labeling spatiotemporal remote sensing datasets M Sethi, Y Yan, A Rangarajan, RR Vatsavai, S Ranka | | |
Anand RangarajanProfessor, Dept. of CISE, Univ. of FloridaVerified email at cise.ufl.edu
