PhD Candidate
Research Interests
My research focuses on developing deep learning techniques for the upsampling of point cloud data to enhance the resolution and accuracy of 3D models. I explore both unsupervised and supervised learning approaches, experimenting with various neural network architectures to address the challenges posed by real-world data. By optimizing these models, I aim to create algorithms that effectively densify point clouds while preserving geometric features, ultimately contributing to more accurate and reliable 3D representations for applications like autonomous driving, robotics, and 3D reconstruction.
Education
- M.Sc. Eng., Geomatics Engineering, University of Tehran, Iran
Publications
- Fatholahi, SN., He, H., Wang, L., Syed, A., Li, J., 2021. Monitoring Surface Deformation Over Oilfield Using MT-InSAR and Production Well Data, IGARSS 2021.
- Qing, L., Petrosian, H., Fatholahi, S., Chapman, M., Li, J., 2021. Quantifying Urban Expansion Using Landsat Images and Landscape Metrics: A Case Study of Halton Region, Ontario, Geomatica, 10.1139/geomat-2020-0017.
- Fatholahi, SN., Akhoondzadeh, M., Bahroudi, A., 2020. An Investigation of Surface Deformation Over Oilfield in Southwest Iran (2003-2010) Using InSAR and Physical Modeling, International Journal of Remote Sensing 41 (14), 5355-5370.
- Mahboub, V., Fatholahi, SN., 2020. A Constrained Extended Kalman Filter Based On LS-VCE Formulated By Condition Equations With Prediction of Cross-Covariances, Survey Review, 1-14.
- Fatholahi, S., Gu, Y., Liu, M., Ma, L., Chen, Y., Li, J., 2020. Estimating PM2.5 Concentrations in British Columbia, Canada During Wildfire Season Using Satellite Optical Data, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 5194, 71-79.
- Mahboub, V., Fatholahi, SN., Aghaei, HA., 2019. On General Constrained Extended Kalman Filter Formulated By Condition Equations: Three Algorithms, Survey Review 52 (374), 423-430.