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Seyed Mohammad Hassan Erfani
Seyed Mohammad Hassan Erfani
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
A novel approach to find and optimize bin locations and collection routes using a geographic information system
SMH Erfani, S Danesh, SM Karrabi, R Shad
Waste Management & Research 35 (7), 776-785, 2017
662017
Using applied operations research and geographical information systems to evaluate effective factors in storage service of municipal solid waste management systems
SMH Erfani, S Danesh, SM Karrabi, R Shad, S Nemati
Waste Management 79, 346-355, 2018
322018
ATLANTIS: A benchmark for semantic segmentation of waterbody images
SMH Erfani, Z Wu, X Wu, S Wang, E Goharian
Environmental Modelling & Software 149, 105333, 2022
302022
Statistical analysis of effective variables on the performance of waste storage service using geographical information system and response surface methodology
SMH Erfani, S Danesh, SM Karrabi, M Gheibi, S Nemati
Journal of environmental management 235, 453-462, 2019
252019
Vision-based texture and color analysis of waterbody images using computer vision and deep learning techniques
SMH Erfani, E Goharian
Journal of Hydroinformatics 25 (3), 835-850, 2023
42023
Atex: a benchmark for image classification of water in different waterbodies using deep learning approaches
SMH Erfani, E Goharian
Journal of Water Resources Planning and Management 148 (11), 04022063, 2022
22022
Efficient semi-supervised surface crack segmentation with small datasets based on consistency regularisation and pseudo-labelling
EA Shamsabadi, SMH Erfani, C Xu, D Dias-da-Costa
Automation in Construction 158, 105181, 2024
12024
Developing a Vision-Based Framework for Measuring and Monitoring Water Resource Systems Using Computer Vision and Deep Learning Techniques
SMH Erfani
University of South Carolina, 2023
12023
Harnessing Heterogeneous Sources of Data and Artificial Intelligence for Hydrologic Monitoring
E Goharian, SMH Erfani, MH Goloujeh
EGU24, 2024
2024
Unraveling patterns in river geometry: Multi-model machine learning for continental-scale predictions
SY Chang, Z Ghahremani, L Manuel, M Erfani, C Shen, S Cohen, ...
AGU23, 2023
2023
River geometry estimation under bankfull and mean flow conditions over the Contiguous United States (CONUS) using Machine Learning (ML) techniques
R Zarrabi, R McDermott, S Cohen, M Erfani
AGU23, 2023
2023
Estimation of Channel Shape for the CONUS Using Regression and Machine Learning Approaches
R McDermott, R Zarrabi, S Cohen, M Erfani
AGU23, 2023
2023
A Large Dataset of Fluvial Hydraulic and Geometry Attributes Derived from USGS field measurement records
M Erfani, M Erfani, S Cohen, E Goharian
AGU23, 2023
2023
The geometry of flow: Advancing predictions of river geometry with multi-model machine learning
SY Chang, Z Ghahremani, L Manuel, M Erfani, C Shen, S Cohen, ...
arXiv preprint arXiv:2312.11476, 2023
2023
Eye of Horus: A Vision-based Framework for Real-time Water Level Measurement
SMH Erfani, C Smith, Z Wu, EA Shamsabadi, F Khatami, ARJ Downey, ...
Authorea Preprints, 2023
2023
A Vision-based Framework for Monitoring and Measurement of Water Depth
SMH Erfani, E Goharian
Fall Meeting 2022, H42C-1263, 2022
2022
Deep Learning-based Models for Estimating River Channel Width
SMH Erfani, Z Ghahremani, L Manuel, SY Chang, E Goharian, JL Pierce, ...
Fall Meeting 2022, H32R-1147, 2022
2022
Data Driven Approaches for Estimating River Channel Geometry over the Continental United States
SY Chang, Z Ghahremani, L Manuel, M Erfani, KJ Van Meter, EA Meselhe, ...
AGU Fall Meeting Abstracts 2022, H52B-05, 2022
2022
Vision-based Analysis of Water, a Shapeless and Transparent Object
SMH Erfani, E Goharian
South Carolina Environmental Conference (SCEC) 2022, 2022
2022
ATeX: A Benchmark for Image Textures Analysis of Water in Different Waterbodies
M Erfani, E Goharian
AGU Fall Meeting Abstracts 2021, H25K-1169, 2021
2021
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