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Seyed Mohammad Hassan Erfani

University of South Carolina

3 papers hereh-index 6219 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • physics.ao-ph1
  • physics.geo-ph1
affiliations
  • University of South Carolina
Homepage

identity via Semantic Scholar / OpenAlex

activity
20212025
most citedThe geometry of flow: Advancing predictions of river geometry with multi-model machine learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

physics.ao-ph2025

Interactive Atmospheric Composition Emulation for Next-Generation Earth System Models

Seyed Mohammad Hassan Erfani, Kara Lamb, Susanne Bauer +3

Interactive composition simulations in Earth System Models (ESMs) are computationally expensive as they transport numerous gaseous and aerosol tracers at each timestep. This limits…

physics.geo-ph2023★ 1 cited

The geometry of flow: Advancing predictions of river geometry with multi-model machine learning

Shuyu Y Chang, Zahra Ghahremani, Laura Manuel +7

Hydraulic geometry parameters describing river hydrogeomorphic is important for flood forecasting. Although well-established, power-law hydraulic geometry curves have been widely u…

cs.CV2021

ATLANTIS: A Benchmark for Semantic Segmentation of Waterbody Images

Seyed Mohammad Hassan Erfani, Zhenyao Wu, Xinyi Wu +2

Vision-based semantic segmentation of waterbodies and nearby related objects provides important information for managing water resources and handling flooding emergency. However, t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.