Saeid Homayouni

Associate Professor

Institut national de la recherche scientifique

Canada

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Saeid Homayouni is an Associate Professor at the Institut national de la recherche scientifique in Canada. His research focuses on advancements in remote sensing and machine learning applications, evident from his recent publications on high-resolution methane prediction, vehicle counting, and wetland mapping. He employs innovative methodologies, including convolutional neural networks and deep learning algorithms, to enhance environmental monitoring and resource management.

Saeid Homayouni

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Articles (19)

Real-Time Moving Vehicle Counting and Speed Estimation Toward Efficient Traffic Surveillance

Machine Learning-Based Alfalfa Height Estimation Using Sentinel-2 Multispectral Imagery

High-Resolution Daily XCH4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data

Integrating Local and Global Features in a Convolutional Vision Transformer for Wetland Mapping

Multiscale Deformable DenseNet for Wetland Mapping Using Hyperspectral Images

Proposing an Efficient Deep Learning Algorithm Based on Segment Anything Model for Detection and Tracking of Vehicles through Uncalibrated Urban Traffic Surveillance Cameras

Machine Learning-Based Lithological Mapping from ASTER Remote-Sensing Imagery

Forest Change Mapping using Multi-Source Satellite SAR, Optical, and LiDAR Remote Sensing Data

Evaluation of Polarimetric SAR Despeckling Methods for Crop Classification from RCM Compact Polarimetry Data

An enhanced descriptor extraction algorithm for power line detection from point clouds

D-Net: A Density-Based Convolutional Neural Network for Mobile LiDAR Point Clouds Classification in Urban Areas

A deep convolutional neural network for burn progression mapping using Sentinel-1 SAR time-series

Mangrove plantation suitability mapping by integrating multi criteria decision making geospatial approach and remote sensing data

An Unsupervised Saliency-Guided Deep Convolutional Neural Network for Accurate Burn Mapping from Sentinel-1 SAR Data

FLOOD SUSCEPTIBILITY MODELLING USING GEOSPATIAL-BASED MULTI-CRITERIA DECISION MAKING IN LARGE SCALE AREAS

IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING

MEASURING SPATIAL ACCESSIBILITY TO HEALTHCARE FACILITIES IN ISFAHAN METROPOLITAN AREA IN IRAN

POINTNET++ TRANSFER LEARNING FOR TREE EXTRACTION FROM MOBILE LIDAR POINT CLOUDS

WHEAT BIOMASS ESTIMATION FROM UAV IMAGERY USING AN ENSEMBLE LEARNING APPROACH WITH BAYESIAN OPTIMIZATION

Collaborators (6)

Alireza Shams

Christian Larouche

Karem Chokmani

Gavin McArdle

Sadegh Jamali

Heidar Rastiveis

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